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At least 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Elementary Particle Physics

The UT Dallas High Energy Physics group collaborates on the ATLAS experiment which observes the world’s high energy proton-proton collisions. The UTD group utilized ATLAS 8 TeV Run 1 data to search for evidence of a “dark photon”, a gauge boson outside the “Standard Model of Particle Physics” that theorist hypothesize could mediate a force felt only by the dark matter particles that dominate out universe. The observable signature is a pair of prompt lepton jets. The results of this search were published in 2013. More recently, we have improved the sensitivity of the analysis using machine learning techniques, and we are extending the search to higher and lower mass dark photons using the ATLAS 13 TeV data set. Detection of a new fifth force would represent an important advance beyond the 4 known forces that influence baryonic matter. The LHC Long Shutdown 1 from 2013-2014 was a period of intense work on refurbishment and upgrades for the ATLAS Pixel community and the UTD group. The service quarter panels of the original Pixel detector were replaced, and the Insertable B Layer (IBL) detector was integrated. During IBL integration, UTD participated on the Stave Task Force that solved corrosion problems with IBL wire bonds. We developed a relative humidity sensor that was used during integration and transport to the beamline when detector was unpowered. The sensors were repurposed to monitor relative humidity inside the ID endplates until the built-in sensors were recommissioned. The UTD group worked on the connection of the Pixel and IBL at Point 1 and we were in charge of electric service testing. The IBL wire bond corrosion was the instigation for developing a new conformal coating method using an atomizing spray and Cellpack polyurethane. It is being considered for use in the ITk tracker upgrade. We have demonstrated its tolerance both of a 9 MGy ionizing dose and thermal expansion. Two UTD students are completing authorship qualification projects. One is helping understand variations in impact parameter resolution across different running periods. The second is developing a data-driven method to monitor the fraction of fake tracks in dense jets.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

The ETROC Project: Precision Timing ASIC Development for LGAD-based CMS Endcap Timing Layer (ETL) Upgrade

The ETROC (Endcap Timing Readout Chip) is being developed for the LGAD-based CMS Endcap Timing Layer (ETL) at HL-LHC. The ETL on each side of the interaction region will be instrumented with a two-disk system of MIP-sensitive LGAD silicon devices to be read out by ETROCs for precision timing measurement with down to 30 ps timing resolution. The ETROC is designed to handle a 16 x 16 pixel cell matrix, with each pixel cell being 1.3 mm x 1.3 mm to match the LGAD sensor pixel size. Approximately 15% of the sensors near the highest eta region will experience hadron fluence above 1e15 neq/cm² towards end of operation of HL-LHC, resulting in small signal amplitude with LGAD gain reduced to around 10. For this reason, the front-end design for preamplifier and discriminator has been specifically optimized for the reduced LGAD signals, with enough flexibilities to meet the ETL specific needs for time resolution, power budget and radiation profile.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

A New CIERRA Gridded Product Climatology for LIS/OTD

The GLM-CIERRA processing generates two products: A level-2 cluster feature dataset that merges flashes that should have been a single flash following the clustering algorithm flash definition (for GLM, this is due to the LCFA thresholds); A set of level-3 gridded products including Flash Extent Density, Convective Probability, etc. The CIERRA Level-3 products are generated on a 0.1 degree grid. This is suboptimal given the spatial variations in GLM pixel size AND the size of gridpoints in the output grid. As a stepping-stone towards developing improved GLM-CIERRA grids, I am testing pixel matching techniques on the LIS/OTD data. The goal is to maintain accuracy while vastly improving computational efficiency. The CIERRA reclustering codes are also being applied to LIS / OTD to merge flashes split by the “first fit” clustering technique. The end result will be standardized grids at the nominal resolution of each instrument (5 km for LIS, 10 km for OTD) that take into account the pixel geometry for each event that comprises a given reclustered flash.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Ultra low background time projection alpha particle detector ( Phase II Final Scientific/Technical Report)

When alpha particles are emitted into a gas they create an ionization track of gas ions and electrons. In our commercial UltraLo instrument we apply a voltage between a planar sample and an anode, integrate the anode signal as it collects the electrons, and distinguish between alphas emitted from the sample and elsewhere (anode, sidewalls) by the duration and shape of the resultant signal. The major contributors limiting the instrument’s lower detection limit are cosmic rays that pass through the detector close to the sample and Rn decays that produce charge tracks the originate in the gas and end on the sample. In this work we proposed to identify and reject these events by converting the anode into a multi-pixel array and operating in time projection mode. Cosmic rays would be eliminated by generating charge on many pixels, while charge collection asymmetry would distinguish between sample events (Bragg curve up) and Rn events (Bragg curve down). We therefore proposed to modify an UltraLo by pixilating its anode, developing low noise, low power multiplexed electronics to track each pixel’s signal individually, and develop analysis software to make the required discriminations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Chamber Interior Viewing System (CIVS 2.0)

The NIF facility is used to conduct fusion and high-density scientific research. The experiments are conducted inside of a 10-meter diameter vacuum chamber called the “Target Chamber”. The target chamber is covered in ports to permit adding equipment to the exterior. Some of this equipment extends into the target chamber such as the target positioners and diagnostics. Other equipment sits on the surface and looks inward, such as the CIVS system. CIVS stands for Chamber Interior Viewing System. The CIVS system provides simple black and white digital images of the interior of the target chamber in real time. These images are used for positioner alignment, trouble shooting and observing for positioner collision. The views through these cameras need to be clear enough for the operators to safely conduct these tasks. One of the products of the experiments conducted in the target chamber are neutrons. These neutrons expand outward from the center of the target chamber with great energy. If the neutrons hit the sensor chip on a digital camera they will “kill” the sensor pixel where they contact, and the result will be a permanently bright white pixel on the image. Over time these “dead” pixels will build up and make the camera less and less usable providing a “staticky” image. The current solution of replacing the cameras when they become damaged is unsustainable due to both the cameras being out of production and the increased rate of camera failure based upon the increased number and energy of neutrons being generated. Current supplies of the correct camera type are dwindling with no source of replacement and the projected rate of replacement is unsustainable. Without a redesign, the function provided by the current CIVS system will be lost.

42 ENGINEERING↗
DOE OSTI2024

Characterization of ORNL PSD ASIC

The performance of the ORNL ASIC and its readout system was tested with pixelated organic scintillators. We use a pixelated trans-Stilbene scintillator array from Inrad Optics and a pixelated organic glass scintillator array developed at Sandia National Laboratories to characterize the energy and timing resolutions and the pulse-shape discrimination (PSD) figure-of-merit (FoM). The results are compared to previous work in which the same metrics were measured on waveforms digitized at 250 MHz with 14-bit resolution. We found that the PSD FoM at 340 keVee of the ASIC configuration compared to waveform data varied with the scintillator type. We measured a PSD FoM of 1.12 ± 0.14 with the ASIC configuration versus 1.39 ± 0.23 with waveform data using the trans-Stilbene array. We measured a PSD FoM of 0.52 ± 0.18 with the ASIC configuration versus 1.25 ± 0.19 with waveform data using the the organic glass scintillator array. The coincidence timing resolution was measured using two 6x6x6 mm 3 cubes of trans-Stilbene. It was measured to be 805 ± 9 ps with the ASIC configuration versus 300 ps on average with waveform data.

42 ENGINEERING↗
DOE OSTI2025

Dense Image Matching Uncertainty Estimation and Confidence Metrics

Dense stereo matching takes overlapping image pairs as input and outputs a disparity map which encodes pixel-by-pixel matches between the images. Recently, there has been an interest in ranking the quality, or even quantifying the accuracy, of disparity estimates. The proposed methods can be described as either uncertainty estimators or confidence metrics. Uncertainty estimators are a small minority of the research. However, they have the potential to be the most useful because they estimate disparity accuracy (in pixel units) that can be used to threshold matches or carried forward using error propagation. The majority of the research deals with confidence metrics which give an ordinal (or binary) ranking of a match’s quality relative to other matches. Confidence metrics do not have units and thus are useful primarily for thresholding matches from mismatches. The methods could also be described as handcrafted or deep-learning based. The majority of the research focused on outdoor driving scenes. Hence, our interest–application to a satellite semi-global matching pipeline–is a domain shift that may challenge deep-learning based methods. We conclude by recommending five handcrafted and two deep-learning based methods for evaluation in our pipeline.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Digital Silicon Photomultiplier Chip Testing

Silicon Photomultipliers (SiPMs) are highly sensitive photodetectors. Traditional analog SiPMs require complex external readout electronics. Digital SiPMs (dSiPMs) include digital readout circuitry directly on-chip, offering superior timing resolution, reduced power consumption and compact size, pixel-level masking for active noise reduction. The primary objectives of this study are to, verify digital logic integrity of the shift registers used for controlling the pixel masking circuit, and determine the dark count rate of individual pixels as a function of bias voltage and clock frequency. I observe and explain behavior of the shift register and counting circuit.

Graham, Bennett [U. Chicago (main)]↗
DOE OSTI2026

DECAL MDN Resolution Calibration

The simulated pixelated calorimeter uses 0.1 mm × 0.1 mm silicon pixels (0.0001 cm²) silicon pixels as active layers — far finer than current concepts like HGCAL (~0.5 cm²) — improving energy resolution through much finer segmentation. While the standard resolution formalism fits three numbers to a handful of discrete test-beam energies, this work is a first try at a more data-efficient alternative: learning the full response shape continuously in energy with a mixture density network. This continuous, differentiable surrogate is a natural building block for fast simulation of extremely complex calorimeters.

Wang, Peter [U. Chicago (main)]↗
DOE OSTI2025

Performance of the AstroPix Prototype Module for the Barrel Imaging Calorimeter at the ePIC Detector and in Space-Based Payloads

AstroPix is a high-voltage CMOS (HV-CMOS) monolithic active pixel sensor originally developed to enable precision gamma-ray imaging and spectroscopy in the medium-energy regime (~100 keV–100 MeV) based on the groundwork laid by ATLASpix and MuPix. It features a 500 μm pixel pitch, in-pixel amplification and digitization, and low power consumption (~3-4 mW/cm2), making it scalable for large-area, multilayer telescope detector planes. The detectors have a designed dynamic range of 25 keV to 700 keV. With these features, AstroPix meets the requirements of future space-based high-energy telescopes and the imaging layers of the Barrel Imaging Calorimeter (BIC) in the Electron-Proton/Ion Collider (ePIC) detector at the future Electron-Ion Collider (EIC). For the space-based payload, AstroPix is being integrated into sounding rocket and balloon payloads to demonstrate the technical readiness of the devices. For BIC, AstroPix-based imaging layers interleaved within the lead/scintillating-fiber (Pb/SciFi) sampling calorimeter provide granular shower imaging, enabling key performance features such as electron/pion or gamma/neutral pion separation. As part of the ongoing detector R&D efforts, we have been testing various AstroPix_v3 configurations: the single chip, a quad-chip assembly, a three-layer stack of quad chips, and a 9-chip module that represents the smallest prototype unit of the BIC imaging layer. This presentation will highlight recent performance test results from these AstroPix detector configurations.

Kim, Bobae (ORCID:0000000295396815)↗
DOE OSTI2021

SLOPE daily and 250 m gross primary productivity (GPP) for the CONUS, 2000-2019, Carbon Monitoring System (CMS)

The SatelLite Only Photosynthesis Estimation (SLOPE) GPP product is a daily, 250 m GPP dataset covering the Contiguous United States (CONUS) from 2000 to present with 1 day latency. Gross primary productivity (GPP) quantifies the amount of carbon dioxide (CO2) fixed by plants through photosynthesis. Although as a key quantity of terrestrial ecosystems, there is a lack of high-spatial-and-temporal-resolution, real-time, and observation-based GPP products. This product has been developed to address this critical gap, leveraging a number of MODIS land and atmosphere products. There are three distinct features of the SLOPE GPP production algorithm. (1) SLOPE couples machine learning models with MODIS atmosphere and land products to accurately estimate PAR. (2) SLOPE couples highly efficient and pragmatic gap-filling and filtering algorithms with surface reflectance acquired by both Terra and Aqua MODIS satellites to derive a soil-adjusted NIRv (SANIRv) dataset. (3) SLOPE couples a temporal pattern recognition approach with a long-term Crop Data Layer (CDL) product to predict dynamic C4 crop fraction. PAR, SANIRv and C4 fraction are used to drive a parsimonious model with only two slope parameters to estimate GPP along with a quantitative uncertainty on a per-pixel and daily basis. The slope GPP product has a R2 = 0.84 and a root-mean-square error (RMSE) of 1.65 gC m-2 d-1, evaluated against from 50 AmeriFlux eddy covariance sites (332 site-years). Archived data from 2000 to 2019 are publicly available at the NASA's Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC). Data from 2020 are available from the authors upon request. All data are projected in the standard MODIS Land Integerized Sinusoidal tile map projection. Each processing tile is in size of 4800 pixels by 4800 pixels, representing approximately 1200 km by 1200 km land region. In addition to the GPP product, SLOPE PAR, SANIRV, and C4 fraction, along with their uncertainties, are also released.

Jiang, Chongya↗
DOE OSTI2017

Diffraction-Based Optical Switching with MEMS

In this article, we are presenting an overview of MEMS-based (Micro-Electro-Mechanical System) optical switch technology starting from the reflective two-dimensional (2D) and three-dimensional (3D) MEMS implementations. To further increase the speed of the MEMS from these devices, the mirror size needs to be reduced. Small mirror size prevents efficient reflection but favors a diffraction-based approach. Two implementations have been demonstrated, one using the Texas Instruments DLP (Digital Light Processing), and the other an LCoS-based (Liquid Crystal on Silicon) SLM (Spatial Light Modulator). These switches demonstrated the benefit of diffraction, by independently achieving high speed, efficiency, and high number of ports. We also demonstrated for the first time that PSK (Phase Shift Keying) modulation format can be used with diffraction-based devices. To be truly effective in diffraction mode, the MEMS pixels should modulate the phase of the incident light. We are presenting our past and current efforts to manufacture a new type of MEMS where the pixels are moving in the vertical direction. The original structure is a 32 x 32 phase modulator array with high contrast grating pixels, and we are introducing a new sub-wavelength linear array capable of a 310 kHz modulation rate

36 MATERIALS SCIENCE↗
DOE OSTI2015

ENTROPY VS. ENERGY WAVEFORM PROCESSING: A COMPARISON ON THE HEAT EQUATION

Virtually all modern imaging devices function by collecting either electromagnetic or acoustic backscattered waves and using the energy carried by these waves to determine pixel values that build up what is basically an ”energy” picture. However, waves also carry ”informa- tion” that also may be used to compute the pixel values in an image. We have employed several measures of information, all of which are based on different forms of entropy. Numerous published studies have demonstrated the advantages of entropy, or “information imaging”, over conventional methods for materials characterization and medical imaging. Similar results also have been obtained with microwaves. The most sensitive information measure appears to be the joint entropy of the backscattered wave and a reference signal. A typical study is comprised of repeated acquisition of backscattered waves from a specimen that is changing slowing with acquisition time or location. The sensitivity of repeated experimental observations of such a slowly changing quantity may be defined as the mean variation (i.e., observed change) divided by mean variance (i.e., observed noise). We compute the sensitivity for joint entropy and signal energy measurements assuming that noise is Gaussian and using Wiener integration to compute the required mean values and variances. These can be written as solutions to the Heat equation, which permits estimation of their magnitudes. There always exists a reference such that joint entropy has larger variation and smaller variance than the corresponding quantities for signal energy, matching observations of several studies. Moreover, a general prescription for finding an “optimal” reference for the joint entropy emerges, which also has been validated in several studies.

Entropy↗
DOE OSTI2023

Automated Quantification of Wind Turbine Blade Leading Edge Erosion from Field Images

Wind turbine blade leading edge erosion is a major source of power production loss and early detection benefits optimization of repair strategies. Two machine learning (ML) models are developed and evaluated for automated quantification of the areal extent, morphology and nature (deep, shallow) of damage from field images. The supervised ML model employs convolutional neural networks (CNN) and learns features (specific types of damage) present in an annotated set of training images. The unsupervised approach aggregates pixel intensity thresholding with calculation of pixel-by-pixel shadow ratio (PTS) to independently identify features within images. The models are developed and tested using a dataset of 140 field images. The images sample across a range of blade orientation, aspect ratio, lighting and resolution. Each model (CNN v PTS) is applied to quantify the percent area of the visible blade that is damaged and classifies the damage into deep or shallow using only the images as input. Both models successfully identify approximately 65% of total damage area in the independent images, and both perform better at quantifying deep damage. The CNN is more successful at identifying shallow damage and exhibits better performance when applied to the images after they are preprocessed to a common blade orientation.

Aird, Jeanie A.↗
DOE OSTI2018

Event Centroiding Applied to Energy-Resolved Neutron Imaging at LANSCE

The energy-dependence of the neutron cross section provides vastly different contrast mechanisms than polychromatic neutron radiography if neutron energies can be selected for imaging applications. In recent years, energy-resolved neutron imaging (ERNI) with epi-thermal neutrons, utilizing neutron absorption resonances for contrast as well as for quantitative density measurements, was pioneered at the Flight Path 5 beam line at LANSCE and continues to be refined. In this work, we present event centroiding, i.e., the determination of the center-of-gravity of a detection event on an imaging detector to allow sub-pixel spatial resolution and apply it to the many frames collected for energy-resolved neutron imaging at a pulsed neutron source. While event centroiding was demonstrated at thermal neutron sources, it has not been applied to energy-resolved neutron imaging, where the energy resolution requires to be preserved, and we present a quantification of the possible resolution as a function of neutron energy. For the 55 μm pixel size of the detector used for this study, we found a resolution improvement from ~80 μm to ~22 μm using pixel centroiding while fully preserving the energy resolution.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Corn response to climate stress detected with satellite-based NDVI time series

Corn growth conditions and yield are closely dependent on climate variability. Leaf growth, measured as the leaf area index, can be used to identify changes in crop growth in response to climate stress. This research was conducted to capture patterns of spatial and temporal corn leaf growth under climate stress for the St. Joseph River watershed, in northeastern Indiana. Leaf growth is represented by the Normalized Difference Vegetative Index (NDVI) retrieved from multiple years (2000–2010) of Landsat 5 TM images. By comparing NDVI values for individual image dates with the derived normal curve, the response of crop growth to environmental factors is quantified as NDVI residuals. Regression analysis revealed a significant relationship between yield and NDVI residual during the pre-silking period, indicating that NDVI residuals reflect crop stress in the early growing period that impacts yield. Both the mean NDVI residuals and the percentage of image pixels where corn was under stress (risky pixel rate) are significantly correlated with water stress. Dry weather is prone to hamper potential crop growth, with stress affecting most of the observed corn pixels in the area. Oversupply of rainfall at the end of the growing season was not found to have a measurable effect on crop growth, while above normal precipitation earlier in the growing season reduces the risk of yield loss at the watershed scale. Furthermore, the spatial extent of stress is much lower when precipitation is above normal than under dry conditions, masking the impact of small areas of yield loss at the watershed scale.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Cleaning Images with Gaussian Process Regression

Many approaches to astronomical data reduction and analysis cannot tolerate missing data: corrupted pixels must first have their values imputed. This paper presents astrofix, a robust and flexible image imputation algorithm based on Gaussian process regression. Through an optimization process, astrofix chooses and applies a different interpolation kernel to each image, using a training set extracted automatically from that image. It naturally handles clusters of bad pixels and image edges and adapts to various instruments and image types. For bright pixels, the mean absolute error of astrofix is several times smaller than that of median replacement and interpolation by a Gaussian kernel. We demonstrate good performance on both imaging and spectroscopic data, including the SBIG 6303 0.4 m telescope and the FLOYDS spectrograph of Las Cumbres Observatory and the CHARIS integral-field spectrograph on the Subaru Telescope.

42 ENGINEERING↗
DOE OSTI2017

Topology of Large-scale Structures of Galaxies in Two Dimensions—Systematic Effects

We study the two-dimensional topology of galactic distribution when projected onto two-dimensional spherical shells. Using the latest Horizon Run 4 simulation data, we construct the genus of the two-dimensional field and consider how this statistic is affected by late-time nonlinear effects—principally gravitational collapse and redshift space distortion (RSD). We also consider systematic and numerical artifacts, such as shot noise, galaxy bias, and finite pixel effects. We model the systematics using a Hermite polynomial expansion and perform a comprehensive analysis of known effects on the two-dimensional genus, with a view toward using the statistic for cosmological parameter estimation. We find that the finite pixel effect is dominated by an amplitude drop and can be made less than 1% by adopting pixels smaller than 1/3 of the angular smoothing length. Nonlinear gravitational evolution introduces time-dependent coefficients of the zeroth, first, and second Hermite polynomials, but the genus amplitude changes by less than 1% between z = 1 and z = 0 for smoothing scales R{sub G}>9 Mpc/h. Non-zero terms are measured up to third order in the Hermite polynomial expansion when studying RSD. Differences in the shapes of the genus curves in real and redshift space are small when we adopt thick redshift shells, but the amplitude change remains a significant ∼O(10%) effect. The combined effects of galaxy biasing and shot noise produce systematic effects up to the second Hermite polynomial. It is shown that, when sampling, the use of galaxy mass cuts significantly reduces the effect of shot noise relative to random sampling.

79 ASTRONOMY AND ASTROPHYSICS↗