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At least 631 records · Page 35

SU-G-IeP3-08: Image Reconstruction for Scanning Imaging System Based On Shape-Modulated Point Spreading Function

Purpose: Deconvolution is a widely used tool in the field of image reconstruction algorithm when the linear imaging system has been blurred by the imperfect system transfer function. However, due to the nature of Gaussian-liked distribution for point spread function (PSF), the components with coherent high frequency in the image are hard to restored in most of the previous scanning imaging system, even the relatively accurate PSF is acquired. We propose a novel method for deconvolution of images which are obtained by using shape-modulated PSF. Methods: We use two different types of PSF - Gaussian shape and donut shape - to convolute the original image in order to simulate the process of scanning imaging. By employing deconvolution of the two images with corresponding given priors, the image quality of the deblurred images are compared. Then we find the critical size of the donut shape compared with the Gaussian shape which has similar deconvolution results. Through calculation of tightened focusing process using radially polarized beam, such size of donut is achievable under same conditions. Results: The effects of different relative size of donut and Gaussian shapes are investigated. When the full width at half maximum (FWHM) ratio of donut and Gaussian shape is set about 1.83, similar resolution results are obtained through our deconvolution method. Decreasing the size of donut will favor the deconvolution method. A mask with both amplitude and phase modulation is used to create a donut-shaped PSF compared with the non-modulated Gaussian PSF. Donut with size smaller than our critical value is obtained. Conclusion: The utility of donutshaped PSF are proved useful and achievable in the imaging and deconvolution processing, which is expected to have potential practical applications in high resolution imaging for biological samples.

60 APPLIED LIFE SCIENCES↗

deeplenstronomy: A dataset simulation package for strong gravitational lensing

Automated searches for strong gravitational lensing in optical imaging survey datasets often employ machine learning and deep learning approaches. These techniques require more example systems to train the algorithms than have presently been discovered, which creates a need for simulated images as training dataset supplements. This work introduces and summarizes deeplenstronomy, an open-source Python package that enables efficient, large-scale, and reproducible simulation of images of astronomical systems. A full suite of unit tests, documentation, and example notebooks are available at https://deepskies.github.io/deeplenstronomy/ .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Water Film Structure during Rupture as Revealed by MDS Image Analysis

The structure of thin water films during the rupture process was investigated by a new approach, which combines molecular dynamics simulation (MDS) with image processing analysis. The analysis procedure was developed to convert MDS trajectories to readable 3D images. The water films were studied at different thicknesses by MDS to determine the critical thickness at which the film ruptures. The potential energy of each specific film thickness during the simulation time was analyzed, and the results showed that the potential energy of stable films remained unchanged while the potential energy kept decreasing for films which ruptured during the simulation time. By applying the new procedure, the molecular porosity, which is defined as the void fraction between the volume of molecular pores in the water film and the total volume of the water film, was calculated. The results of molecular porosity for different film thicknesses during the simulation time suggested a critical molecular porosity as 49%. In other words, stable films have a molecular porosity of less than 49%. If a water film has a molecular porosity greater than 49%, rupture occurs during the simulation. This research was supported by the US Department of Energy, Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences.

molecular dynamics simulation, film stability, ima↗

Searching for Subsecond Stellar Variability with Wide-field Star Trails and Deep Learning

We present here a method that enables wide-field ground-based telescopes to scan the sky for subsecond stellar variability. The method has operational and image processing components. The operational component takes star trail images. Each trail serves as a light curve for its corresponding source and facilitates subexposure photometry. We train a deep neural network to identify stellar variability in wide-field star trail images. We use the Large Synoptic Survey Telescope Photon Simulator to generate simulated star trail images and include transient bursts as a proxy for variability. The network identifies transient bursts on timescales down to 10 ms. We argue that there are multiple fields of astrophysics that can be advanced by the unique combination of time resolution and observing throughput that our method offers.

79 ASTRONOMY AND ASTROPHYSICS↗

Low-Mass Planar Photonic Imaging Sensor

Continuing on the successful progress of NIAC Phase I, this report summarizes the technical progress achieved under NIAC Phase II during the performance period September 19, 2014-June 18, 2017. During this period, the research team has made the following accomplishments: designed and layout a silica photonic integrated circuit (PIC) as a two baseline interferometric imager; constructed an experiment to utilize the two baselines for complex visibility measurement on a point source and a variable width slit; analyzed and studied the testbed results. (in collaboration with Lockheed Martin); designed and layout Si3N4 PICs for the low-resolution and high-resolution SPIDER telescope; fabricated the multi-layer Si3N4 PIC for low and high resolution SPIDER telescope; characterize the optical throughput and heater response for Si3N4 PIC for low and high resolution SPIDER telescopes; carried out imaging experiments using the Si3N4 PIC low-resolution version (in collaboration with Lockheed Martin); investigated signal-to-noise (SNR) ratio of SPIDER imager compared to the conventional panchromatic imager (in collaboration with Lockheed Martin); fulfilled the SNR simulation upon SPIDER imager (in collaboration with Lockheed Martin).

Yoo, S. J. Ben↗

Low-Mass Planar Photonic Imaging Sensor

Continuing on the successful progress of NIAC (NASA Innovative Advanced Concepts) Phase I, this report summarizes the technical progress achieved under NIAC Phase II during the performance period September 19, 2014 to June 18, 2017. During this period, the research team has made the following accomplishments: designed and layout a silica photonic integrated circuit (PIC) as a two baselineinterferometric imager; constructed an experiment to utilize the two baselines for complex visibility measurementon a point source and a variable width slit; analyzed and studied the testbed results (in collaboration with Lockheed Martin); designed and layout Si3N4 PICs for the low-resolution and high-resolution SPIDER (Segmented Planar Imaging Detector for Electro-Optical Reconnaissance) telescope; fabricated the multi-layer Si3N4 PIC for low and high resolution SPIDER telescope; characterized the optical throughput and heater response for Si3N4 PIC for low and highresolution SPIDER telescopes; carried out imaging experiments using the Si3N4 PIC low-resolution version (in collaboration with Lockheed Martin); investigated signal-to-noise (SNR) ratio of SPIDER imager compared to the conventional panchromatic imager (in collaboration with Lockheed Martin); fulfilled the SNR simulation upon SPIDER imager (in collaboration with Lockheed Martin).

Yoo, S. J. Ben↗

3D micromechanical simulation of PBX composites

Previous research studied the constitutive response and interface strength of a bonded bicrystal system containing two HMX explosive grains bound with a HTPB polymer binder by performing FE simulations on real geometry imaged with micro Computed Tomography (µCT). The parameters generated from this past study were successfully applied to 2D mesoscale simulations of µCT imaged HMX-HTPB polycrystal samples. Presently, the mechanical response of PBXs containing a Nitro-Plasticized Estane (NPE) binder with similar microstructural geometry to the HMX-HTPB polycrystal samples were studied. Imaging of a HMX-NPE bicrystal sample allowed for simulation of the new material pairing. However, imaging using µCT techniques on the new polycrystal samples was difficult due to the decrease in contrast between the HMX grains and the NPE binder. Mesoscale polycrystal simulations utilizing a single µCT imaged microstructure were performed on a 3D representative volume element (RVE) comparing the delamination behavior and mechanical response of both HMX-HTPB and HMX-NPE PBXs. Furthermore, this technique shows the ability to virtually explore the mechanical response of a range of hypothetical materials that share common microstructural geometric characteristics in addition to studying numerically altered geometries.

36 MATERIALS SCIENCE↗

Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components (Final Technical Report)

Metal Additive Manufacturing (AM) is a promising method for cost-efficient fabrication of complex shape structures for applications in harsh environment, such as in a nuclear reactor. However, internal defects (pores) occur in high-strength AM alloys, which are manufactured with Laser Powder Bed Fusion (LPBF) AM method. Pulsed Infrared Thermography (PIT) is an efficient nondestructive evaluation (NDE) method to examine actual structures, because this method offers one-sided non-contact measurements, and fast processing of large sample areas. However, imaging of material defects, particularly defects with sizes at microscopic level, is challenging. In this report, we benchmark the performance of several Unsupervised Learning (UL) algorithms designed to enhance imaging of microscopic defects in metals with PIT. UL aims to learn the latent principal patterns (dictionaries) in PIT data to detect defects with minimal human supervision. Performance of Independent Component Analysis (ICA), Sparse Coding (SC), Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) was compared using F-score, UL model training time and defects reconstruction time. We obtained the average F-score of 0.75, and a highest F-score of 0.89 for the EFA algorithm. Overall, EFA outperforms other UL algorithms considered in this study. In another approach, we investigate Thermal Tomography (TT), which is a computational method for reconstruction of depth profile of internal material defects from PIT nondestructive evaluation (NDE). TT algorithm obtains depth reconstructions of thermal effusivity, which has been shown to provide visualization of subsurface internals defects in metals. In many applications, one needs to determine the defect shape and orientation from reconstructed effusivity images. Interpretation of TT images is non-trivial because of blurring, which increases with depth due to heat diffusion-based nature of image formation. We have developed a deep learning convolutional neural network (CNN) to classify size and orientation of subsurface material defects in TT images. CNN was trained with TT images produced with computer simulations of 2D metallic structures (thin plates) containing elliptical subsurface voids. Performance of CNN was investigated using test TT images developed with computer simulations of plates containing elliptical defects, and defects with shape imported from scanning electron microscopy (SEM) images. CNN demonstrated the ability to classify radii and angular orientation of elliptical defects in previously unseen test TT images. We have also demonstrated that CNN trained on TT images of elliptical defects is capable of classifying shape and orientation of irregular defects. Training the CNN on irregular defect shapes instead of on elliptical shapes would make the resulting classifications more descriptive of actual defect shapes. However, this requires a much higher volume of SEM images of material defects, which are difficult to obtain because of random occurrence of defects in LPBF. To address this challenge, we developed a generative adversarial network (GAN) to augment the existing dataset of SEM defect images. The GAN model is demonstrated to create novel yet realistic defect shapes that can be used as input for simulated PTT images to train CNN. We also investigate several approaches based on Gaussian Random Circle and Bezier Curves for constructing parametric models of irregular-shape defects.

36 MATERIALS SCIENCE↗

Monte Carlo Simulations of Background Spectra in Integral Imager Detectors

Predictions of the expected gamma-ray backgrounds in the ISGRI (CdTe) and PiCsIT (Csl) detectors on INTEGRAL due to cosmic-ray interactions and the diffuse gamma-ray background have been made using a coupled set of Monte Carlo radiation transport codes (HETC, FLUKA, EGS4, and MORSE) and a detailed, 3-D mass model of the spacecraft and detector assemblies. The simulations include both the prompt background component from induced hadronic and electromagnetic cascades and the delayed component due to emissions from induced radioactivity. Background spectra have been obtained with and without the use of active (BGO) shielding and charged particle rejection to evaluate the effectiveness of anticoincidence counting on background rejection.

Armstrong, T. W.↗

Improved Interactive Medical-Imaging System

An improved computational-simulation system for interactive medical imaging has been invented. The system displays high-resolution, three-dimensional-appearing images of anatomical objects based on data acquired by such techniques as computed tomography (CT) and magnetic-resonance imaging (MRI). The system enables users to manipulate the data to obtain a variety of views for example, to display cross sections in specified planes or to rotate images about specified axes. Relative to prior such systems, this system offers enhanced capabilities for synthesizing images of surgical cuts and for collaboration by users at multiple, remote computing sites.

Ross, Muriel D.↗

What can we learn from in-soil imaging of a live plant: X-ray Computed Tomography and 3D numerical simulation of root-soil system

Plant roots play a critical role in plant-soil-microbe interactions that occur in the rhizosphere, as well as processes with important implications to farming, forest management and climate change. X-ray computed tomography (XCT) has been proven to be an effective tool for non-invasive root imaging and analysis. A combination of XCT, open-source software, and our own code was used to noninvasively image a prairie dropseed (Sporobolus heterolepis) specimen, segment the root data to obtain a 3D image of the root structure at 31µm resolution, and extract quantitative information (root volume and surface area) from the 3D data, respectively. Based on the mesh generated from the root structure, computational fluid dynamics (CFD) simulations were applied to numerically investigate the root-soil-groundwater system. The plant root conductivity, soil hydraulic conductivity and transpiration rate were shown to control the groundwater distribution. The flow variability and soil water distributions under different scenarios were investigated. Parameterizations were evaluated to show their impacts on the average conductivity. The pore-scale modeling approach provides realistic simulations of rhizosphere flow processes and provides useful information that can be linked to upscaled models.

54 ENVIRONMENTAL SCIENCES↗

Two-temperature GRRMHD Simulations of M87

Here, we present axisymmetric two-temperature general relativistic radiation magnetohydrodynamic simulations of the inner region of the accretion flow onto the supermassive black hole M87. We address uncertainties from previous modeling efforts through inclusion of models for (1) self-consistent dissipative and Coulomb electron heating (2) radiation transport (3) frequency-dependent synchrotron emission, self-absorption, and Compton scattering. We adopt a distance D = 16.7 Mpc, an observer angle θ = 20°, and consider black hole masses M/M ⊙ = (3.3 x 10 9 , 6.2 x 10 9 ) and spins a star = (0.5, 0.9375) in a four-simulation suite. For each (M, a star ), we identify the accretion rate that recovers the 230 GHz flux from very long baseline interferometry measurements. We report on disk thermodynamics at these accretion rates (M · /M · Edd ~ 10 -5 ). The disk remains geometrically thick; cooling does not lead to a thin disk component. While electron heating is dominated by Coulomb rather than dissipation for r ≳ 10GM/c 2 , the accretion disk remains two-temperature. Radiative cooling of electrons is not negligible, especially for r ≲ 10GM/c 2 . The Compton y parameter is of order unity. We then compare derived and observed or inferred spectra, millimeter images, and jet powers. Simulations with M/M ⊙ = 3.3 × 10 9 are in conflict with observations. These simulations produce millimeter images that are too small, while the low-spin simulation also overproduces X-rays. For M/M ⊙ = 6.2 x 10 9 , both simulations agree with constraints on radio/IR/X-ray fluxes and millimeter image sizes. Simulation jet power is a factor 10 2 –10 3 below inferred values, a possible consequence of the modest net magnetic flux in our models.

79 ASTRONOMY AND ASTROPHYSICS↗

Simulations of Hayabusa2 Atmospheric Entry and Comparisons with Data from the Imaging Campaign

Results from flow and radiation simulations for the Hayabusa2 Sample Return Capsule (SRC) along its best-estimated trajectory (BET) are presented. Flow fields are first computed at several points along the best-estimated trajectory for a freestream consisting of N2, O2, Ar, CO2, and H2O; the last three are trace species in Earth’s atmosphere. The thermal response of an assumed ablative material is estimated and flow fields are recomputed at each time point with modified surface temperature distributions. The spectral radiance, from the combination of an aeroheated capsule and the high-temperature shock layer around it, is computed on an imaging plane for a given view angle and slant range at each time point. The radiance is transported through the intervening atmosphere between the Hayabusa2 SRC and the observing aircraft and upon integration over solid angle representing the field of view of the instruments converted to a spectral irradiance. The spectral irradiance is convolved with the instrument function to obtain results that can be directly compared with measurement. Fair to good comparisons with measurements required shifting the time coordinate of measurements by 7.5 s. The disagreement between prediction and measurement is substantial after about 72.5 s along the BET. Additional computations seem to support the idea of flow transition over the capsule.

Atmospheric entry↗

Simulations of Hayabusa2 Atmospheric Entry and Comparisons with Data from the Imaging Campaign

Results from flow and radiation simulations for the Hayabusa2 Sample Return Capsule (SRC) along its best-estimated trajectory (BET) are presented. Flow fields are first computed at several points along the best-estimated trajectory for a freestream consisting of N2, O2, Ar, CO2, and H2O; the last three are trace species in Earth’s atmosphere. The thermal response of an assumed ablative material is estimated and flow fields are recomputed at each time point with modified surface temperature distributions. The spectral radiance, from the combination of an aeroheated capsule and the high-temperature shock layer around it, is computed on an imaging plane for a given view angle and slant range at each time point. The radiance is transported through the intervening atmosphere between the Hayabusa2 SRC and the observing aircraft and upon integration over solid angle representing the field of view of the instruments converted to a spectral irradiance. The spectral irradiance is convolved with the instrument function to obtain results that can be directly compared with measurement. Fair to good comparisons with measurements required shifting the time coordinate of measurements by 7.5 s. The disagreement between prediction and measurement is substantial after about 72.5 s along the BET. Additional computations seem to support the idea of flow transition over the capsule.

Atmospheric entry↗

Simulation of ASTER data using AVIRIS images

The Advanced Thermal Emission and Reflectance Radiometer (ASTER) is a joint Japanese/US imaging instrument scheduled to fly on the first Earth Observing System (EOS) platform in 1998. The complement of scanners includes a visible, three channel module with forward-looking stereo capability, a six channel short wavelength infrared module, and a five channel thermal module. As part of the definition phase for the instrument design, AVIRIS data was used to simulate the short wave infrared (SWIR) bands to investigate the effects of widening two of the bands to increase the signal-to-noise ratio (SNR) versus loss of spectral separability due to uncertainty in the post-launch band positions.

Abrams, Michael↗

Dark fluxes from electromagnetic cascades

We study dark sector production in electromagnetic (EM) cascades. This problem requires accurate simulations of Standard Model (SM) and dark sector processes, both of which impact angular and energy distributions of emitted particles that ultimately determine flux predictions in a downstream detector. We describe the minimal set of QED processes which must be included to faithfully reproduce a SM cascade, and identify a universal algorithm to generate a dark sector flux given a Monte-Carlo simulation of a SM shower. We provide a new tool, "Image missing", which simulates EM cascades with associated dark vector production, and compare it against existing literature and “off the shelf” tools. The signal predictions at downstream detectors can strongly depend on the nontrivial interplay (and modelling) of SM and dark sector processes, in particular multiple Coulomb scattering and positron annihilation. We comment on potential impacts of these effects for realistic experimental setups.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Physical interpretation and development of ultrasonic nondestructive evaluation techniques applied to the quantitative characterization of textile composite materials

In this Progress Report, the author describes the continuing research to explore the feasibility of implementing medical linear array imaging technology as a viable ultrasonic-based nondestructive evaluation method to inspect and characterize complex materials. Images obtained using an unmodified medical ultrasonic imaging system of a bonded aluminum plate sample with a simulated disbond region are presented. The disbond region was produced by adhering a piece of plain white paper to a piece of cellophane tape and applying the paper-tape combination to one of the aluminum plates. Because the area under the paper was not adhesively bonded to the aluminum plate, this arrangement more closely simulates a disbond. Images are also presented for an aluminum plate sample with an epoxy strip adhered to one side to help provide information for the interpretation of the images of the bonded aluminum plate sample containing the disbond region. These images are compared with corresponding conventional ultrasonic contact transducer measurements in order to provide information regarding the nature of the disbonded region. The results of this on-going investigation may provide a step toward the development of a rapid, real-time, and portable method of ultrasonic inspection and characterization based on linear array technology. In Section 2 of this Progress Report, the preparation of the aluminum plate specimens is described. Section 3 describes the method of linear array imaging. Sections 4 and 5 present the linear array images and results from contact transducer measurements, respectively. A discussion of the results are presented in Section 6.

Miller, James G.↗

3D Cloud Radiative Effects on Aerosol Optical Thickness Retrievals in Cumulus Cloud Fields in the Biomass Burning Region in Brazil

Aerosol amount in clear regions of a cloudy atmosphere is a critical parameter in studying the interaction between aerosols and clouds. Since the global cloud cover is about 50%, cloudy scenes are often encountered in any satellite images. Aerosols are more or less transparent, while clouds are extremely reflective in the visible spectrum of solar radiation. The radiative transfer in clear-cloudy condition is highly three- dimensional (3D). This paper focuses on estimating the 3D effects on aerosol optical thickness retrievals using Monte Carlo simulations. An ASTER image of cumulus cloud fields in the biomass burning region in Brazil is simulated in this study. The MODIS products (i-e., cloud optical thickness, particle effective radius, cloud top pressure, surface reflectance, etc.) are used to construct the cloud property and surface reflectance fields. To estimate the cloud 3-D effects, we assume a plane-parallel stratification of aerosol properties in the 60 km x 60 km ASTER image. The simulated solar radiation at the top of the atmosphere is compared with plane-parallel calculations. Furthermore, the 3D cloud radiative effects on aerosol optical thickness retrieval are estimated.

Wen, Guo-Yong↗