Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “image coding”

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 1,243 records · Page 69

Optical Characterization of a Multipoint Lean Direct Injector for Gas Turbine Combustors: Velocity and Fuel Drop Size Measurements

Performance of a multipoint, lean direct injection (MP-LDI) strategy for low emission aero-propulsion systems has been tested in a Jet-A fueled, lean flame tube combustion rig. Operating conditions for the series of tests included inlet air temperatures between 672 and 828 K, pressures between 1034 and 1379 kPa and total equivalence ratios between 0.41 and 0.45, resulting in equilibrium flame temperatures approaching 1800 K. Ranges of operation were selected to represent the spectrum of subsonic and supersonic flight conditions projected for the next-generation of commercial aircraft. This document reports laser-based measurements of in situ fuel velocities and fuel drop sizes for the NASA 9-point LDI hardware arranged in a 3 3 square grid configuration. Data obtained represent a region of the flame tube combustor with optical access that extends 38.1-mm downstream of the fuel injection site. All data were obtained within reacting flows, without particle seeding. Two diagnostic methods were employed to evaluate the resulting flow path. Three-component velocity fields have been captured using phase Doppler interferometry (PDI), and two-component velocity distributions using planar particle image velocimetry (PIV). Data from these techniques have also offered insight into fuel drop size and distribution, fuel injector spray angle and pattern, turbulence intensity, degree of vaporization and extent of reaction. This research serves to characterize operation of the baseline NASA 9- point LDI strategy for potential use in future gas-turbine combustor applications. An additional motive is the compilation of a comprehensive database to facilitate understanding of combustor fuel injector aerodynamics and fuel vaporization processes, which in turn may be used to validate computational fluid dynamics codes, such as the National Combustor Code (NCC), among others.

Heath, Christopher M.↗

Catalyst-Vision (PEM Catalyst Layer Image Analysis Tool) [SWR-25-100]

Catalyst-Vision (PEM Catalyst Layer Image Analysis Tool) provides an advanced Python-based tool, primarily designed for use in a Jupyter/Colab notebook, for the quantitative morphological analysis of pre-segmented shapes. While developed for analyzing PEM catalyst layers from microscopy, its methodology is suitable for characterizing any grayscale object provided on a uniform white background. The tool uses a robust computer vision pipeline based on the Euclidean Distance Transform and skeletonization to accurately measure local thickness and tortuosity, providing a comprehensive characterization of an object's geometry and internal texture. If you find this code useful, please cite our preprint as: Chan, Ai-Lin and Hayden, Steven and Harvey, Steven P. and Smeaton, Michelle and Okrucky, Caleb and Watt, John and Ulična, Soňa and Spurgeon, Steven and Jungjohann, Katherine and Alia, Shaun, Mechanism-informed breakdown: understanding degradation by controlling voltage hold patterns in PEM water electrolyzers. Preprint (2025).

Spurgeon, Steven [National Laboratory of the Rocki↗

Vegetation classification map and covariates associated with NEON AOP survey, East River, CO 2018

This package includes geospatial data layers developed to investigate how environmental gradients—specifically topography and near-surface soil properties—drive the spatial arrangement of dominant plant communities in mountainous watersheds. The geospatial products, which support the analysis of these ecological relationships, are derived from airborne hyperspectral and LiDAR datasets acquired by the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP), in conjunction with an extensive ground field campaign conducted in summer 2018. This work is part of the DOE Watershed Function Science Focus Area (SFA) and features geospatial datasets developed based on observations and ground data collected at East River, Colorado, in collaboration with the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) survey in June 2018. Classification Map: - Classification Map (PNG, GeoTIFF): Derived from hyperspectral and LiDAR airborne data using a machine learning approach. - Class Code Mapper (CSV): Associates pixel values with corresponding vegetation/non-vegetation classes. - Classification Reference Data (CSV): Reference data used in the machine learning procedure. LiDAR-Derived Products: - Topographical Metrics (GeoTIFFs): Elevation, slope, curvature, TWI, TPI, solar insolation, and canopy height model (CHM), smoothed with a 5x5 pixel window. Vegetation Indices: - GeoTIFFs of NDVI, NDNI, NDWI: Vegetation indices derived from hyperspectral data. Urban Masks: - Urban Mask (GeoTIFF): Applied to the mapping to convert bare soil classes to urban classes. Software Compatibility: GeoTIFFs: Can be visualized with GIS software or libraries that support GeoTIFF images. CSV Files: Can be opened with any software that handles comma-separated values. The FLMD file provides details and links to the source datasets used to derive the products. The manuscript (in the Method session) provides details on how each product was derived. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. Update on 2026-03-25: Since the original dataset publication date of 02/28/2020, this package has a new classification map derived by an improved methodology. This update also includes additional ground data that improved the representation of some of the communities. See the methods for further details on what has changed between versions.

2018 NEON and 2025 CHESS Campaigns↗

w22_laser_radiography - Laser-Based MeV Radiography

This project seeks to develop novel x-ray sources based on high-power short-pulse lasers with unique advantages, including small spot size, flexible configuration, and tailorable spectra. Kinetic plasma simulations using the VPIC particle in cell code will be performed to support the R&D goals of this project. If successful, this effort will allow LANL to deploy flexible, compact x-ray sources for static tomographic radiography and dynamic multi-axis radiography at our firing sites and facilities such as pRad and U1a. The higher resolution, shorter pulse duration, and tunability of our proposed sources will enable new applications in the weapons program and broader scientific community. This effort advances the LANL FY22 Strategic Investment Plan priority of “[r]adiographic tools for dynamic and static imaging with improved spatial and temporal resolution, sensitivity, and dose.”

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

The Impacts of Recent Drought on Fire, Forest Loss, and Regional Smoke Emissions in Lowland Bolivia

In the southern Amazon relationships have been established among drought, human activities that cause forest loss, fire, and smoke emissions. We explore the impacts of recent drought on fire, forest loss, and atmospheric visibility in lowland Bolivia. To assess human influence on fire, we consider climate, fire, and vegetation dynamics in an area largely excluded from human activities since 1979, Noel Kempff Mercado National Park (NK) in northeastern Bolivia. We use data from five sources: the Moderate Resolution Imaging Spectroradiometer Collection 6 active fire product (2001-2015) (MODIS C6), Global Fire Weather Database (GFWED) data (1982-2015), MODIS land cover data (2001-2010), MODIS forest loss data (2000-2012), and the regional extinction coefficient for the southwestern Amazon (i.e., B(sub ext)), which is derived from horizontal visibility data from surface stations at the World Meteorological Organization (WMO) level (1973-2015). The B(sub ext) is affected by smoke and acts as a proxy for visibility and regional fire emissions. In lowland Bolivia from 2001 to 2015, interannual Drought Code (DC) variability was linked to fire activity, while from 1982 to 2015, interannual DC variability was linked to B(sub ext). From 2001 to 2015, the B(sub ext) and MODIS C6 active fire data for lowland Bolivia captured fire seasonality, and covaried between low- and high-fire years. Consistent with previous studies, our results suggest B(sub ext)t can be used as a longer-term proxy of regional fire emissions in southwestern Amazonia. Overall, our study found drought conditions were the dominant control on interannual fire variability in lowland Bolivia, and fires within NK were limited to the Cerrado and seasonally inundated wetland biomes. Our results suggest lowland Bolivian tropical forests were susceptible to human activities that may have amplified fire during drought. Human activities and drought need to be considered in future projections of southern Amazonian fire, in regard to carbon emissions and global climate.

Forest Loss↗

Computational strategies for tire monitoring and analysis

Computational strategies are presented for the modeling and analysis of tires in contact with pavement. A procedure is introduced for simple and accurate determination of tire cross-sectional geometric characteristics from a digitally scanned image. Three new strategies for reducing the computational effort in the finite element solution of tire-pavement contact are also presented. These strategies take advantage of the observation that footprint loads do not usually stimulate a significant tire response away from the pavement contact region. The finite element strategies differ in their level of approximation and required amount of computer resources. The effectiveness of the strategies is demonstrated by numerical examples of frictionless and frictional contact of the space shuttle Orbiter nose-gear tire. Both an in-house research code and a commercial finite element code are used in the numerical studies.

Danielson, Kent T.↗

The COR1 Inner Coronagraph for STEREO-SECCHI

The Solar Terrestrial Relations Observatory (STEREO) is a pair of identical satellites that will orbit the Sun so as to drift ahead of and behind Earth respectively, to give a stereo view of the Sun. STEREO is currently scheduled for launch in November 2005. One of the instrument packages that will be own on each of the STEREO spacecrafts is the Sun Earth Connection Coronal and Heliospheric Investigation (SECCHI), which consists of an extreme ultraviolet imager, two coronagraphs, and two side-viewing heliospheric imagers to observe solar coronal mass ejections all the way from the Sun to Earth. We report here on the inner coronagraph, labeled COR1. COR1 is a classic Lyot internally occulting refractive coronagraph, adapted for the first time to be used in space. The field of view is from 1.3 to 4 solar radii. A linear polarizer is used to suppress scattered light, and to extract the polarized brightness signal from the solar corona. The optical scattering performance of the coronagraph was first modeled using both the ASAP and APART numerical modeling codes, and then tested at the Vacuum Tunnel Facility at the National Center for Atmospheric Research in Boulder, Colorado. In this report, we will focus on the COR1 optical design, the predicted optical performance, and the observed performance in the lab. We will also discuss the mechanical and thermal design, and the cleanliness requirements needed to achieve the optical performance.

Thompson, William T.↗

GJ 229B: Solving the Puzzle of the First Known T Dwarf with the APOLLO Retrieval Code

GJ 229B was the first T dwarf to be discovered in 1995, and its spectrum has been more thoroughly observed than that of most other brown dwarfs. Yet a full spectroscopic analysis of its atmosphere has not been done with modern techniques. This spectrum has several peculiar features, and recent dynamical estimates of GJ 229B’s mass and orbit have disagreed widely, both of which warrant closer investigation. With a separation of tens of astronomical units from its host star, GJ 229B falls near the border of the planet and stellar population formation regimes, so its atmosphere could provide clues to formation processes for intermediate objects of this type. In an effort to resolve these questions, we performed retrievals on published spectra of GJ 229B over a wide range of wavelengths (0.5–5.1 μm) using the open-source APOLLO code. Based on these retrievals, we present a more precise mass estimate of 41.6 ± 3.3MJ and an effective temperature estimate of 869 +5 −7 K, which are more consistent with evolutionary models for brown dwarfs and suggest an older age for the system of >1.0 Gyr. We also present retrieved molecular abundances for the atmosphere, including replicating the previously observed high CO abundance, and discuss their implications for the formation and evolution of this object. This retrieval effort will give us insight into how to study other brown dwarfs and directly imaged planets, including those observed with JWST and other next-generation telescopes.

Alex R Howe↗

Photometric Properties of Quiet Sun Observed With the DKIST and HINODE

The variability of irradiance is primarily influenced by surface magnetism, such as sunspots, faculae, and network structures. Each of these features contributes differently to the overall variability. However, the impact of small magnetic elements, which are commonly observed in high resolution images of the solar photosphere but remain unresolved in full-disk images used for irradiance modeling, is still a topic of debate. Understanding the influence of these small magnetic elements to the overall brightness, particularly in quiet regions, is fundamental to understanding irradiance fluctuations over decadal and longer temporal scales. We investigate the brightness of small-size magnetic elements using very high spatial resolution spectro-polarimetric observations acquired at different spectral ranges with the National Science Foundations Daniel K. Inouye Solar Telescope (DKIST) and with HINODE/SOT. Our results are compared to 3D MHD Small Solar Dynamo simulations obtained with the MURaM code.

SMD↗

Current Issues in Unsteady Turbomachinery Flows (Images)

Among the numerous causes for unsteadiness in turbo machinery flows are turbulence and flow environment, wakes from stationary and rotating vanes, boundary layer separation, boundary layer/shear layer instabilities, presence of shock waves and deliberate unsteadiness for flow control purposes. These unsteady phenomena may lead to flow-structure interactions such as flutter and forced vibration as well as system instabilities such as stall and surge. A major issue of unsteadiness relates to the fact that a fundamental understanding of unsteady flow physics is lacking and requires continued attention. Accurate simulations and sufficient high fidelity experimental data are not available. The Glenn Research Center plan for Engine Component Flow Physics Modeling is part of the NASA 21st Century Aircraft Program. The main components of the plan include Low Pressure Turbine National Combustor Code. The goals, technical output and benefits/impacts of each element are described in the presentation. The specific areas selected for discussion in this presentation are blade wake interactions, flow control, and combustor exit turbulence and modeling.

Povinelli, Louis↗

High-performance data management for whole slide image analysis in digital pathology

When dealing with giga-pixel digital pathology in whole-slide imaging, a notable proportion of data records holds relevance during each analysis operation. For instance, when deploying an image analysis algorithm on whole-slide images (WSI), the computational bottleneck often lies in the input-output (I/O) system. This is particularly notable as patch-level processing introduces a considerable I/O load onto the computer system. However, this data management process could be further paralleled, given the typical independence of patch-level image processes across different patches. This paper details our endeavors in tackling this data access challenge by implementing the Adaptable IO System version 2 (ADIOS2). Our focus has been constructing and releasing a digital pathology-centric pipeline using ADIOS2, which facilitates streamlined data management across WSIs. Additionally, we’ve developed strategies aimed at curtailing data retrieval times. The performance evaluation encompasses two key scenarios: (1) a pure CPU-based image analysis scenario (“CPU scenario”), and (2) a GPU-based deep learning framework scenario (“GPU scenario”). Our findings reveal noteworthy outcomes. Under the CPU scenario, ADIOS2 showcases an impressive two-fold speed-up compared to the brute-force approach. In the GPU scenario, its performance stands on par with the cutting-edge GPU I/O acceleration framework, NVIDIA Magnum IO GPU Direct Storage (GDS). From what we know, this appears to be among the initial instances, if any, of utilizing ADIOS2 within the field of digital pathology. The source code has been made publicly available at https://github.com/hrlblab/adios.

Wang, Xiao↗

Conflation of Geospatial POI Data and Ground-level Imagery

The code solves the problem of conflating POI (Points of Interest) geospatial data and geo-tagged ground-level imagery data. The main challenges with fusion or conflation of these two types of data has been that these two data entities are represented not only in several ways in current state-of-the-art, but also there is mismatch of representation format of these two data types. This source code/software brings POI datapoints and ground-level imagery datapoints into same representation format, and then generates valuable Knowledge Graph combining POI and images data (so that it can be used for multitude of applications).

De, Debraj↗

High-Contrast Near-Infrared Imaging Polarimetry of the Protoplanetary Disk around RY Tau

We present near-infrared coronagraphic imaging polarimetry of RY Tau. The scattered light in the circumstellar environment was imaged at H-band at a high resolution (approx. 0.05) for the first time, using Subaru-HiCIAO. The observed polarized intensity (PI) distribution shows a butterfly-like distribution of bright emission with an angular scale similar to the disk observed at millimeter wavelengths. This distribution is offset toward the blueshifted jet, indicating the presence of a geometrically thick disk or a remnant envelope, and therefore the earliest stage of the Class II evolutionary phase. We perform comparisons between the observed PI distribution and disk models with: (1) full radiative transfer code, using the spectral energy distribution (SED) to constrain the disk parameters; and (2) monochromatic simulations of scattered light which explore a wide range of parameters space to constrain the disk and dust parameters. We show that these models cannot consistently explain the observed PI distribution, SED, and the viewing angle inferred by millimeter interferometry. We suggest that the scattered light in the near-infrared is associated with an optically thin and geometrically thick layer above the disk surface, with the surface responsible for the infrared SED. Half of the scattered light and thermal radiation in this layer illuminates the disk surface, and this process may significantly affect the thermal structure of the disk.

protoplanetary disks↗

Staged Z-pinch experiment at the double-EAGLE pulsed power facility

The staged Z-pinch is a potential high-energy gain fusion concept where a high atomic number liner implodes on a deuterium target using a pulsed multi-MA current source. Over the past several years this concept has been studied on 0.5–1.0 MA facilities using Ar and Kr gas puffs injected at R = 1.2 cm. Neutron yield up to (2.5 ± 0.34) x 10 10 was measured, Ruskov et al (2023 IEEE Trans. Plasma Sci. 51 3310–6). Here, in this study, we present experimental results from the 4 MA, 110 ns current rise time Double-EAGLE facility at L3Harris (currently, Fisica Inc.) where a larger radius nozzle created gas density profiles peaked at R = 2.5 cm. Modeling with the MACH2 and FLASH codes indicates that the larger radius allows stronger acceleration of the liner plasma and generation of shock waves that preheat a target plasma layer next to the liner to temperatures $T_i >$1 keV. The resulting counter thermal pressure on the liner plasma limits the growth of the Magneto-Rayleigh–Taylor (MRT) instability at the liner-vacuum boundary and the implosion proceeds in a relatively stable manner. Near bang time the enormous target plasma thermal pressure smoothens the MRT perturbations developed during the earlier implosion stages. Time integrated x-ray pinhole images with cutoff energy of 100 eV confirm that a long (∼3 cm), stable and uniform high energy density plasma column is formed in the final implosion stage. Consistent neutron yield in the 10 10 –10 11 range was measured for both Ar and Kr liners imploding on a deuterium target.

Physics - Plasma physics↗

Probe microscopy is all you need *

We pose that microscopy offers an ideal real-world experimental environment for the development and deployment of active Bayesian and reinforcement learning methods. Indeed, the tremendous progress achieved by machine learning (ML) and artificial intelligence over the last decade has been largely achieved via the utilization of static data sets, from the paradigmatic MNIST to the bespoke corpora of text and image data used to train large models such as GPT3, DALL·E and others. However, it is now recognized that continuous, minute improvements to state-of-the-art do not necessarily translate to advances in real-world applications. We argue that a promising pathway for the development of ML methods is via the route of domain-specific deployable algorithms in areas such as electron and scanning probe microscopy and chemical imaging. This will benefit both fundamental physical studies and serve as a test bed for more complex autonomous systems such as robotics and manufacturing. Favorable environment characteristics of scanning and electron microscopy include low risk, extensive availability of domain-specific priors and rewards, relatively small effects of exogenous variables, and often the presence of both upstream first principles as well as downstream learnable physical models for both statics and dynamics. Recent developments in programmable interfaces, edge computing, and access to application programming interfaces (APIs) facilitating microscope control, all render the deployment of ML codes on operational microscopes straightforward. We discuss these considerations and hope that these arguments will lead to create novel set of development targets for the ML community by accelerating both real world ML applications and scientific progress.

47 OTHER INSTRUMENTATION↗

Using Polarized PCRTM-Solar Model to Validate EMIT Surface Reflectance L2A Product

Using the vector linearized discrete ordinate radiative transfer model (VLIDORT), a multiple-scattering multi-layer scattering code, coupled with a fast principal component (PC) radiative transfer model (PCRTM), we can simulate hyperspectral radiation fields from visible to shortwave infrared (VSWIR), i.e., 250 nm to 2500 nm. Since only limited accurate line-by-line calculation using VLIDORT is needed, this coupled PCRTM-VLIDORT approach is very efficient for simulating hyperspectral VSWIR spectra. These simulations incorporate accurately defined optical properties (gas absorptions, molecular and aerosol/cloud particle scattering) and detailed surface reflectance inputs. In this study we used the current L2A products of the Earth Surface Mineral Dust Source Investigation (EMIT) imaging spectrometer as the inputs to PCRTM-VLIDORT to simulate EMIT spectra. Comparing the simulated spectra with EMIT measurements provides an efficient method to validate the current EMIT product.

Xiaozhen Xiong↗

Uncertainty-aware Continuous Implicit Neural Representations for Remote Sensing Object Counting

Many existing object counting methods rely on density map estimation (DME) of the discrete grid representation by decoding extracted image semantic features from designed convolutional neural networks (CNNs). Relying on discrete density maps not only leads to information loss dependent on the original image resolution, but also has a scalability issue when analyzing high-resolution images with cubically increasing memory complexity. Furthermore, none of the existing methods can offer reliable uncertainty quantification (UQ) for the derived count estimates. To overcome these limitations, we design UNcertainty-aware, hypernetwork-based Implicit neural representations for Counting (UNIC) to assign probabilities and the corresponding counting confidence over continuous spatial coordinates. We derive a sampling-based Bayesian counting loss function and develop the corresponding model training algorithm. UNIC outperforms existing methods on the Remote Sensing Object Counting (RSOC) dataset with reliable UQ and improved interpretability of the derived count estimates. Our code is available at https://github.com/SiyuanXu-tamu/UNIC.

97 MATHEMATICS AND COMPUTING↗

Analysis of the Tanana River Basin using LANDSAT data

Digital image classification techniques were used to classify land cover/resource information in the Tanana River Basin of Alaska. Portions of four scenes of LANDSAT digital data were analyzed using computer systems at Ames Research Center in an unsupervised approach to derive cluster statistics. The spectral classes were identified using the IDIMS display and color infrared photography. Classification errors were corrected using stratification procedures. The classification scheme resulted in the following eleven categories; sedimented/shallow water, clear/deep water, coniferous forest, mixed forest, deciduous forest, shrub and grass, bog, alpine tundra, barrens, snow and ice, and cultural features. Color coded maps and acreage summaries of the major land cover categories were generated for selected USGS quadrangles (1:250,000) which lie within the drainage basin. The project was completed within six months.

Morrissey, L. A.↗