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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 55 records · Page 3

Predicting 3D Motions from Single-Camera Optical Test Data

In a typical optical test, a stereo camera pair is required to measure the three-dimensional motion of a test article; one camera typically only measures motions in the image plane of the camera, and measurements in the out-of-plane direction are missing. Finite element expansion techniques provide a path to estimate responses from a test at unmeasured degrees of freedom. Treating the case of a single camera as a measurement with unmeasured degrees of freedom, a finite element model is used to expand to the missing third dimension of the image data, allowing a full-field, three-dimensional measurement to be obtained from a set of images from a single camera. The key to this technique relies on the mapping of finite element deformations to image deformations, creating a set of mode shape images that are used to filter the response in the image into modal responses. These modal responses are then applied to the finite element model to estimate physical responses at all finite element model degrees of freedom. The mapping from finite element model to image is achieved using synthetic images produced by a rendering software. Finally, the technique is applied first to a synthetic deformation image, and then is validated using an experimental set of images.

47 OTHER INSTRUMENTATION↗

Scintillation event imaging with a single photon avalanche diode camera

Position and time measurements of scintillation events encode information about the radiation source. Single photon avalanche diode (SPAD) arrays offer multiple-megapixel spatial resolution and tens of picoseconds temporal resolution for detecting single photons. Current lensless designs for measuring scintillation events use sensors that are lower in spatial resolution. Camera-based designs use sensors that are lower in temporal resolution or readout rate and cannot image individual interactions. Here we propose to image scintillation events in a thick, monolithic scintillator using a high-resolution SPAD camera. We demonstrate that a commercial SPAD camera is able to gather sufficient signal to image individual scintillation events and observe 3D shifts in their spatial distribution. Simulations show that a SPAD camera can localize individual scintillation events in 3D. We report direct imaging of gamma-ray interactions in a scintillator with a SPAD camera. The proposed design may allow to measure complex signatures of individual particles interacting in the scintillator.

47 OTHER INSTRUMENTATION↗

A 1D Lyman-alpha profile camera for plasma edge neutral studies on the DIII-D tokamak

A one dimensional, absolutely calibrated pinhole camera system was installed on the DIII-D tokamak to measure edge Lyman-alpha (Ly-α) emission from hydrogen isotopes, which can be used to infer neutral density and ionization rate profiles. The system is composed of two cameras, each providing a toroidal fan of 20 lines of sight, viewing the plasma edge on the inboard and outboard side of DIII-D. The cameras’ views lie in a horizontal plane 77 cm below the midplane. At its tangency radius, each channel provides a radial resolution of ~2 cm full width at half maximum (FWHM) with a total coverage of 22 cm. Each camera consists of a rectangular pinhole, Ly-α reflective mirror, narrow-band Ly-α transmission filter, and a 20 channel AXUV photodetector. The combined mirror and transmission filter have a FWHM of 5 nm, centered near the Ly-α wavelength of 121.6nm and is capable of rejecting significant, parasitic carbon-III (C-III) emission from intrinsic plasma impurities. To provide a high spatial resolution measurement in a compact footprint, the camera utilizes advanced engineering and manufacturing techniques including 3D printing, high stability mirror mounts, and a novel alignment procedure. Absolutely calibrated, spatially resolved Ly-α brightness measurements utilize a bright, isolated line with low parasitic surface reflections and enable quantitative comparison to modeling to study divertor neutral leakage, main chamber fueling, and radial particle transport.

Ionization Rate↗

A multi-mass and multi-hit two-camera 3D ion momentum imaging system

We demonstrate an improved two-camera system for multi-mass and multi-hit three-dimensional (3D) momentum imaging of ions. The imaging system employs two conventional complementary metal–oxide–semiconductor cameras. We have shown previously that the system can time slice ion Newton spheres with a time resolution of 8.8 ns, limited by camera timing jitter [J. Chem. Phys., 158, 191104 (2023)]. In this work, a jitter correction method was developed to suppress the camera jitter and improve the time resolution to better than 2 ns. With this resolution, full 3D momentum distributions of ions can be obtained. We further show that this method can detect two ions with different masses when utilizing both the rising and falling edges of the cameras.

Instruments & Instrumentation↗

A Nonintrusive Optical Approach to Characterize Heliostats in Utility-Scale Power Tower Plants: Camera Position Sensitivity Analysis

Optics plays a major role in the effectiveness of concentrating solar power (CSP) technologies. The nonintrusive optical (NIO) approach developed by the National Renewable Energy Laboratory uses uncrewed aircraft system (UAS)-based imaging to survey heliostats in a commercial-scale power tower CSP plant and characterize their optical errors. The image processing algorithm uses photogrammetry to calculate the camera position for each image frame, and the accuracy of the estimated optical errors is highly sensitive to the calculated camera position accuracy. In this study, we simulate a series of case studies in python to examine the impact of different parameters of the sensitivity of the camera calculation, including the number of facet corners used as control points for the photogrammetric calculation, precision error in the detected pixel locations of the facet corners in the image, and precision error of the canting and mounting positions of the facets of the heliostat. The case studies consider heliostat geometry based on three commercial designs to serve as representative examples of different possible sizes of heliostats that the NIO method could be applied to. The results show that increasing the number of control points can improve accuracy for heliostats with many facets, pixel precision has a significantly larger impact on camera calculation accuracy than facet canting and mounting errors, and the camera distance and focal length must be chosen to ensure adequate pixel accuracy on the heliostat surface depending on the size of heliostat. In conclusion, based on the results, recommendations for the allowable values of each parameter are provided to achieve the required NIO optical error estimation accuracy depending on the size of heliostat.

14 SOLAR ENERGY↗

Large Game Distribution Camera Study at Los Alamos National Laboratory [Poster]

The unique habitats at the Laboratory support a diverse community of wildlife. The habitat types that include Pinon Juniper, Ponderosa Pine, and Mixed-conifer forests each provide different resources important for a variety of species. Wildlife monitoring for large game animals can be challenging because they avoid interactions with humans, and prefer undeveloped areas. This study was conducted to analyze the distribution of predators and other game animals seasonally across the Laboratory. The data gathered will be used to make recommendations regarding wildlife management for conservation and protection. Utilizing game cameras to remotely monitor wildlife was determined to be the most effective, noninvasive method to gather the necessary data. As camera technology has advanced, game cameras have become adequate for documenting individuals, and are commonly used in wildlife studies on predation, abundance, occupancy, diversity, and endangered species detection. Twenty cameras were placed across the LANL landscape using a modified systematic sampling design. They were deployed in February 2018 and retrieved in January 2019, thus each camera sampled for one full year. All images were reviewed and the species, number, age, and sex of all animals in the photo were recorded. Here we present data for the most abundant species encountered: deer, elk, coyote, bear, bobcat, mountain lion, and fox respectively. The data were summarized by species and season. Future work will include occupancy modelling for each species. This will allow the development of heat maps showing species distributions across the Laboratory.

54 ENVIRONMENTAL SCIENCES↗

Large Game Distribution Camera Study at Los Alamos National Laboratory

The unique habitats at the Laboratory support a diverse community of wildlife. The habitat types that include Pinon Juniper, Ponderosa Pine, and Mixed-conifer forests each provide different resources important for a variety of species. Wildlife monitoring for large game animals can be challenging because they avoid interactions with humans, and prefer undeveloped areas. This study was conducted to analyze the distribution of predators and other game animals seasonally across the Laboratory. This research informs decisions regarding wildlife management recommendations for conservation and protection. This study utilized game cameras to remotely monitor wildlife. As camera technology has advanced, game cameras have become adequate for documenting individuals, and are commonly used in wildlife studies on predation, abundance, occupancy, diversity, and endangered species detection. Twenty cameras were placed across the LANL landscape using a modified systematic sampling design. They were deployed in February 2018 and retrieved in January 2019, thus each camera sampled for one full year. All images were reviewed and the species, number, age, and sex of all animals in the photo were recorded. Here we present data for the most abundant species encountered: deer, elk, coyote, bear, bobcat, mountain lion, and fox respectively. The data were summarized by species and season. Future work will include occupancy modelling for each species. This will allow the development of heat maps showing species distributions across the Laboratory.

59 BASIC BIOLOGICAL SCIENCES↗

Neutron Positioning and Geometric Distortion Correction on the SNS SiPM Anger Camera

Neutron Anger cameras are scintillator-based thermal neutron detectors that utilize pixelated photosensors to read out visible light signals and position neutrons accurately They are versatile detectors that can cover large areas for diffraction instruments and offer high efficiency and sub-millimeter spatial resolution. Photomultiplier Tube (PMT) based cameras are installed on three instruments at Spallation Neutron Source (SNS). The next generation camera uses Silicon Photomultipliers (SiPMs) instead of PMTs, which allows for a more compact design and higher spatial resolution. In this report, the Gaussian least-squares position fitting method is described in detail, as well as the method used to correct for geometric distortions across the face of the camera. Results from neutron camera tests before and after the distortion correction are shown and the spatial resolution is quantified.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A 1D Lyman-alpha Profile Camera for Plasma Edge Neutral Studies on the DIII-D Tokamak

A one dimensional, absolutely calibrated pinhole camera system was installed on the DIII-D tokamak to measure edge Lyman-alpha (Ly-a) emission from hydrogenic isotopes which can be used to infer neutral density and ionization rate proles. The system is composed of two cameras, each providing a toroidal fan of twenty lines of sight, viewing the plasma edge on the inboard and outboard side of DIII-D. The cameras' views lie in a horizontal plane 77 cm below the midplane. At its tangency radius, each channel provides a radial resolution of approximately 2 cm full width at half maximum (FWHM) with a total coverage of 22 cm. Each camera consists of a rectangular pinhole, Ly-a reflective mirror, narrow-band Ly-a transmission fiter, and a 20 channel AXUV photodetector. The combined mirror and transmission fiter have a FWHM of 5 nm, centered near the Ly-a wavelength of 121.6 nm and is capable of rejecting significant, parasitic carbon-III (C-III) emission from intrinsic plasma impurities. To provide a high spatial resolution measurement in a compact footprint, the camera utilizes advanced engineering and manufacturing techniques including 3D printing, high stability mirror mounts, and a novel alignment procedure. Absolutely calibrated, spatially resolved Ly-a brightness measurements utilize a bright, isolated line with low parasitic surface reflections and enable quantitative comparison to modeling to study divertor neutral leakage, main chamber fueling and radial particle transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Clumping index estimation with 30°-tilted cameras in row crops: Evaluation of methods and segment size effects

The clumping index (CI) quantifies the spatial distribution of foliage elements and is essential for accurately estimating the plant area index (PAI), canopy radiative transfer, and photosynthesis. Traditionally, the finite-length averaging method (LX), the gap size distribution method (CC), and a combined approach of CC and LX (CLX) have been applied to instruments like TRAC and digital hemispherical photography to estimate CI. However, a comprehensive evaluation of these methods in row crops remains limited, especially regarding the influence of segment size on CI. Meanwhile, digital cameras offer a cost-effective and user-friendly solution for canopy measurements in row crops, yet their application in this context remains underexplored. In this study, we employed a new approach using a 30°-tilted digital camera to estimate CI in corn and soybean fields, applying the LX, CC, and CLX methods. We systematically assessed the performance of these three methods by combining field measurements in real-world fields with simulations using the LESS 3D radiative transfer model. Our results showed that CLX applied to the whole image and 45° segment offered accurate estimation of CI (bias within ±0.1, RMSE < 0.2) and PAI (bias within ±0.4, RMSE < 1) in real-world fields and LESS simulations. The accuracy of the LX method was highly sensitive to segment size, with the best performance observed at the 15° segment (PAI bias within ±0.4). In contrast, the CC method remained stable across different segment sizes, and its performance was generally comparable to that of LX, except at the 15° segment. Across view zenith angles, CI derived from CC generally showed a continuous increase, while those from LX and CLX followed a rising trend at small zenith angles but began to decline at 68°, likely due to an increasing proportion of no-gap segments. Seasonally, LX tended to show decreasing CI during early growth stages but increased as the canopy matured, whereas CC and CLX showed gradually increasing CI before plateauing at peak PAI. The 30°-tilted camera effectively captured CI variations across different angles and growth stages, making it a practical and robust instrument for row crop canopy structure analysis. Furthermore, applying these CI methods to digital cameras offers a low-cost and accessible CI estimation alternative, improving canopy structure monitoring accuracy in row crops.

30°-tilted camera↗

MHD mode tracking using high-speed cameras and deep learning

Abstract We present a new algorithm to track the amplitude and phase of rotating magnetohydrodynamic (MHD) modes in tokamak plasmas using high speed imaging cameras and deep learning. This algorithm uses a convolutional neural network (CNN) to predict the amplitudes of the n = 1 sine and cosine mode components using solely optical measurements from one or more cameras. The model was trained and tested on an experimental dataset consisting of camera frame images and magnetic-based mode measurements from the High Beta Tokamak - Extended Pulse (HBT-EP) device, and it outperformed other, more conventional, algorithms using identical image inputs. The effect of different input data streams on the accuracy of the model’s predictions is also explored, including using a temporal frame stack or images from two cameras viewing different toroidal regions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Use of a 360-Degree Underwater Camera to Characterize Artificial Reef and Fish Aggregating Effects around Marine Energy Devices

Marine energy devices must be attached to the seafloor by their foundations, pilings, or anchors, and will have other parts in the water column like the devices themselves, mooring lines, and power export cables running along the seafloor. The installation and presence of these artificial structures will create physical changes that can disrupt or create new habitats, and potentially alter the behavior of mobile organisms such as fish around a device by attracting them to these new artificial reefs and fish aggregating devices. In this study, we tested a new approach for monitoring fish activity around a marine energy device anchor: a 360-degree underwater camera to keep the target (a wave energy converter’s anchor) in the field of view of the camera. The camera was deployed in three configurations (hand-held, tripod, video lander) at sites with different hydrodynamics and underwater visibilities. The video lander was the best configuration: very stable, versatile, and easy to handle. The 360-degree field of view enabled observing and counting fishes, which were more abundant at dusk than dawn or noon, around the anchor. Despite remaining challenges, 360-degree cameras are useful tools for monitoring animal interactions with marine energy devices.

360-degree camera↗

Enhancing Camera Calibration for Traffic Surveillance with an Integrated Approach of Genetic Algorithm and Particle Swarm Optimization

Recent advancements in sensor technologies, coupled with signal processing and machine learning, have enabled real-time traffic control systems to effectively adapt to changing traffic conditions. Cameras, as sensors, offer a cost-effective means to determine the number, location, type, and speed of vehicles, aiding decision-making at traffic intersections. However, the effective use of cameras for traffic surveillance requires proper calibration. This paper proposes a new optimization-based method for camera calibration. In this approach, initial calibration parameters are established using the Direct Linear Transformation (DLT) method. Then, optimization algorithms are applied to further refine the calibration parameters for the correction of nonlinear lens distortions. A significant enhancement in the optimization process is achieved through the integration of the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) into a combined Integrated GA and PSO (IGAPSO) technique. The effectiveness of this method is demonstrated through the calibration of eleven roadside cameras at three different intersections. The experimental results show that when compared to the baseline DLT method, the vehicle localization error is reduced by 22.30% with GA, 22.31% with PSO, and 25.51% with IGAPSO.

47 OTHER INSTRUMENTATION↗

Using Machine Learning to Track Objects Across Cameras

Video surveillance is one of the most important technologies used by the International Atomic Energy Agency in international safeguards. At large, complicated facilities, multiple surveillance cameras are deployed to monitor the transfer of safeguards-relevant objects across the site. During inspections, all surveillance videos are reviewed to ensure the objects are not manipulated or diverted during transfer, a laborious, time-consuming task. This work describes using deep machine learning algorithms to track objects automatically across multiple cameras, greatly improving the efficiency of the review process. The fundamental problem in this object tracking task across multiple cameras is how to associate the same object, which may show extreme intra-class variations, such as viewpoints, occlusions, and various scales, in different and even non-overlapped cameras. Object re-identification (Re-ID) in nuclear facility video surveillance is even more challenging than classic person or vehicle Re-ID problems because different instances in the same category may display an identical appearance. One observation from nuclear facility surveillance videos is that all objects must be carted (e.g., via forklift) to move. Therefore, the spatial context information of an object, which provides the feature from the carrier, is critical for the object Re-ID task. This work proposes a two-stream convolutional neural networks model that takes features of objects and their surrounding regions into account. Moreover, the custom videos usually are gleaned from different scenes from the training data, which may have extreme variations in illumination changes and/or cluttered backgrounds. Directly applying the trained model to custom videos will dramatically decrease the performance. To tackle this problem, an advanced domain adaptation technique is proposed to mitigate the gap between the data taken from different scenes. The proposed framework will track objects of interest across a nuclear complex. The resulting tracks can be used in further analyses, such as event/activity recognition, anomaly detection, etc.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Sub-millimeter resolution SiPM-based neutron anger camera

Thermal and cold neutron beamlines require detector systems that have a high neutron efficiency, large active area, and good spatial resolution. One type of detector that has been implemented at beamlines at the Spallation Neutron Source (SNS) is a scintillator-based Anger camera that utilizes photomultiplier tubes (PMTs) as photodetectors. In this work, we present a new Anger camera design that replaces PMTs with silicon photomultipliers (SiPMs). This new design offers better resolution, less distortion, and more compactness than the previous cameras. A camera with active area of ~100 cm 2 was shown to have a spatial resolution better than 0.5 mm. Additionally, the use of SiPMs allows for use in strong magnetic fields, opening the possibility of additional experimental capabilities. In conclusion, prototype has been built that demonstrates vacuum-compatibility, as required for a proposed beamline for the Second Target Station at SNS.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Imaging pyrometry for most color cameras using a triple pass filter

A simple combination of the Planck blackbody emission law, optical filters, and digital image processing is demonstrated to enable most commercial color cameras (still and video) to be used as an imaging pyrometer for flames and explosions. The hardware and data processing described take advantage of the color filter array (CFA) that is deposited on the surface of the light sensor array present in most digital color cameras. In this work, a triple-pass optical filter incorporated into the camera lens allows light in three 10-nm wide bandpass regions to reach the CFA/light sensor array. These bandpass regions are centered over the maxima in the blue, green, and red transmission regions of the CFA, minimizing the spectral overlap of these regions normally present. A computer algorithm is used to retrieve the blue, green, and red image matrices from camera memory and correct for remaining spectral overlap. A second algorithm calibrates the corrected intensities to a gray body emitter of known temperature, producing a color intensity correction factor for the camera/filter system. The Wien approximation to the Planck blackbody emission law is used to construct temperature images from the three color (blue, green, red) matrices. A short pass filter set eliminates light of wavelengths longer than 750 nm, providing reasonable accuracy (±10%) for temperatures between 1200 and 6000 K. The effectiveness of this system is demonstrated by measuring the temperature of several systems for which the temperature is known.

47 OTHER INSTRUMENTATION↗

Multi-camera imaging to characterize jet and liner uniformity on the Plasma Liner Experiment (PLX)

At Plasma Liner Experiment, a set of 36 coaxial plasma guns are deployed quasi-uniformly over a 9 ft diameter spherical chamber and are used to form a high-Z spherically compressive plasma liner. Simulations indicate that for the concept to ultimately achieve optimal target density and temperature, a high degree of timing uniformity is required between all guns. Therefore, to aid in quantifying and correcting gun-to-gun nonuniformities, a key diagnostic will consist of up to six fisheye-view CCD cameras positioned inside the main chamber such that each has all plasma guns within its view. The individual cameras can be triggered at different times to determine each plasma jet’s muzzle velocity and structure for different operating conditions. This camera array is currently under development, and the implementation needs and challenges for this camera array are discussed here. Additionally, we detail the analysis methodology for determining jet-to-jet uniformity deviations and how we can correct them, thereby improving overall liner uniformity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Monte Carlo technique to model performance of streak camera-based time-resolving x-ray spectrometers

A Monte Carlo technique has been developed to simulate the expected signal and the statistical noise of x-ray spectrometers that use streak cameras to achieve the time resolution required for ultrafast diagnostics of laser-generated plasmas. The technique accounts for statistics from both the photons incident on the streak camera’s photocathode and the electrons emitted by the photocathode travelling through the camera’s electron optics to the sensor. We use the technique to optimize the design of a spectrometer, which deduces the temporal history of electron temperature of the hotspot in an inertial confinement fusion implosion from its hard x-ray continuum emission spectra. The technique is general enough to be applied to any instrument using an x-ray streak camera.

Stoupin, S. (ORCID:0000000226225270)↗