Results for “Image Processing” — Page 32

DOE OSTI2016

Bubble-Size Evolution during Polyurethane Foam Expansion

We are developing computational models to elucidate the expansion and dynamic filling process of a polyurethane (PMDI) foam used to encapsulate electronic components or to produce lightweight structural parts. The polyurethane of interest is a chemically blown foam, where carbon dioxide is produced via the reaction of water, a blowing agent, and isocyanate. Here, we take a careful look at the evolution of the bubble sizes during blowing. This information will help the development of subgrid models to predict bubble formation, growth, coalescence and collapse, drainage, and, hence, eventually the development of engineering models to predict foam expansion into a mold. Close-up views of bubbles at a transparent wall of a narrow, temperature-controlled channel are recorded during the foaming reaction and analyzed with image processing. Because these bubbles are pressed against the wall, the bubble sizes in the last frames after the expansion has stopped are compared to scanning electron microscope (SEM) images of the interior of some of the cured samples to determine if the presence of the wall significantly changes the bubble sizes. In addition, diffusing wave spectroscopy (DWS) is used to determine the average bubble sizes across the width of a similar channel as the bubbles change with time. DWS also gives information about microstructural changes as bubbles rearrange upon bubble collapse or coalescence. In this paper we conclude qualitatively that the bubble size distribution is heavily dependent on the formulation of foam being tested, temperature, the height in the foam bar, the proximity to a wall, and the degree of over-packing.

36 MATERIALS SCIENCE↗

DOE OSTI2016

MO-B-201-00: Motion Management in Current Stereotactic Body Radiation Therapy (SBRT) Practice

The motion management in stereotactic body radiation therapy (SBRT) is a key to success for a SBRT program, and still an on-going challenging task. A major factor is that moving structures behave differently than standing structures when examined by imaging modalities, and thus require special considerations and employments. Understanding the motion effects to these different imaging processes is a prerequisite for a decent motion management program. The commonly used motion control techniques to physically restrict tumor motion, if adopted correctly, effectively increase the conformity and accuracy of hypofractionated treatment. The effective application of such requires one to understand the mechanics of the application and the related physiology especially related to respiration. The image-guided radiation beam control, or tumor tracking, further realized the endeavor for precision-targeting. During tumor tracking, the respiratory motion is often constantly monitored by non-ionizing beam sources using the body surface as its surrogate. This then has to synchronize with the actual internal tumor motion. The latter is often accomplished by stereo X-ray imaging or similar techniques. With these advanced technologies, one may drastically reduce the treated volume and increase the clinicians’ confidence for a high fractional ablative radiation dose. However, the challenges in implementing the motion management may not be trivial and is dependent on each clinic case. This session of presentations is intended to provide an overview of the current techniques used in managing the tumor motion in SBRT, specifically for routine lung SBRT, proton based treatments, and newly-developed MR guided RT. Learning Objectives: Through this presentation, the audience will understand basic roles of commonly used imaging modalities for lung cancer studies; familiarize the major advantages and limitations of each discussed motion control methods; familiarize the major advantages and limitations of each discussed radiation beam control methodology and tumor tacking method; understand the key points in motion management for a high quality SBRT program.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

MO-B-201-01: Overcoming the Challenges of Motion Management in Current Lung SBRT Practice

The motion management in stereotactic body radiation therapy (SBRT) is a key to success for a SBRT program, and still an on-going challenging task. A major factor is that moving structures behave differently than standing structures when examined by imaging modalities, and thus require special considerations and employments. Understanding the motion effects to these different imaging processes is a prerequisite for a decent motion management program. The commonly used motion control techniques to physically restrict tumor motion, if adopted correctly, effectively increase the conformity and accuracy of hypofractionated treatment. The effective application of such requires one to understand the mechanics of the application and the related physiology especially related to respiration. The image-guided radiation beam control, or tumor tracking, further realized the endeavor for precision-targeting. During tumor tracking, the respiratory motion is often constantly monitored by non-ionizing beam sources using the body surface as its surrogate. This then has to synchronize with the actual internal tumor motion. The latter is often accomplished by stereo X-ray imaging or similar techniques. With these advanced technologies, one may drastically reduce the treated volume and increase the clinicians’ confidence for a high fractional ablative radiation dose. However, the challenges in implementing the motion management may not be trivial and is dependent on each clinic case. This session of presentations is intended to provide an overview of the current techniques used in managing the tumor motion in SBRT, specifically for routine lung SBRT, proton based treatments, and newly-developed MR guided RT. Learning Objectives: Through this presentation, the audience will understand basic roles of commonly used imaging modalities for lung cancer studies; familiarize the major advantages and limitations of each discussed motion control methods; familiarize the major advantages and limitations of each discussed radiation beam control methodology and tumor tacking method; understand the key points in motion management for a high quality SBRT program.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

MO-B-201-02: Motion Management for Proton Lung SBR

The motion management in stereotactic body radiation therapy (SBRT) is a key to success for a SBRT program, and still an on-going challenging task. A major factor is that moving structures behave differently than standing structures when examined by imaging modalities, and thus require special considerations and employments. Understanding the motion effects to these different imaging processes is a prerequisite for a decent motion management program. The commonly used motion control techniques to physically restrict tumor motion, if adopted correctly, effectively increase the conformity and accuracy of hypofractionated treatment. The effective application of such requires one to understand the mechanics of the application and the related physiology especially related to respiration. The image-guided radiation beam control, or tumor tracking, further realized the endeavor for precision-targeting. During tumor tracking, the respiratory motion is often constantly monitored by non-ionizing beam sources using the body surface as its surrogate. This then has to synchronize with the actual internal tumor motion. The latter is often accomplished by stereo X-ray imaging or similar techniques. With these advanced technologies, one may drastically reduce the treated volume and increase the clinicians’ confidence for a high fractional ablative radiation dose. However, the challenges in implementing the motion management may not be trivial and is dependent on each clinic case. This session of presentations is intended to provide an overview of the current techniques used in managing the tumor motion in SBRT, specifically for routine lung SBRT, proton based treatments, and newly-developed MR guided RT. Learning Objectives: Through this presentation, the audience will understand basic roles of commonly used imaging modalities for lung cancer studies; familiarize the major advantages and limitations of each discussed motion control methods; familiarize the major advantages and limitations of each discussed radiation beam control methodology and tumor tacking method; understand the key points in motion management for a high quality SBRT program.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

MO-B-201-03: MRI-Guided Tracking and Gating

The motion management in stereotactic body radiation therapy (SBRT) is a key to success for a SBRT program, and still an on-going challenging task. A major factor is that moving structures behave differently than standing structures when examined by imaging modalities, and thus require special considerations and employments. Understanding the motion effects to these different imaging processes is a prerequisite for a decent motion management program. The commonly used motion control techniques to physically restrict tumor motion, if adopted correctly, effectively increase the conformity and accuracy of hypofractionated treatment. The effective application of such requires one to understand the mechanics of the application and the related physiology especially related to respiration. The image-guided radiation beam control, or tumor tracking, further realized the endeavor for precision-targeting. During tumor tracking, the respiratory motion is often constantly monitored by non-ionizing beam sources using the body surface as its surrogate. This then has to synchronize with the actual internal tumor motion. The latter is often accomplished by stereo X-ray imaging or similar techniques. With these advanced technologies, one may drastically reduce the treated volume and increase the clinicians’ confidence for a high fractional ablative radiation dose. However, the challenges in implementing the motion management may not be trivial and is dependent on each clinic case. This session of presentations is intended to provide an overview of the current techniques used in managing the tumor motion in SBRT, specifically for routine lung SBRT, proton based treatments, and newly-developed MR guided RT. Learning Objectives: Through this presentation, the audience will understand basic roles of commonly used imaging modalities for lung cancer studies; familiarize the major advantages and limitations of each discussed motion control methods; familiarize the major advantages and limitations of each discussed radiation beam control methodology and tumor tacking method; understand the key points in motion management for a high quality SBRT program.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2026

Design optimization of MAPS-based detectors using a data-driven fast simulation approach

A parametric simulation tool for pixel sensors is presented. A realistic pixel response is simulated purely based on measurement input, without requiring detailed knowledge of the underlying manufacturing process. As such, it provides an efficient alternative to the use of Technology Computer-Aided Design simulations, which typically depend on proprietary process information. Due to its parametric approach, the package is fast and thus particularly useful for larger detector systems and high hit rate environments. This work presents measurements, simulation and its validation for the MALTA2 sensor. It is a small collection electrode monolithic active pixel sensor produced in the Tower 180 nm complementary metal-oxide-semiconductor imaging process. Modifications to the sensor’s periphery, mainly in the hit merger, are studied in order to optimize the performance for tracking and calorimetry. This optimization is of special interest as part of the MALTA3 sensor redesign in the 65 nm Tower Partners Semiconductor Co. process.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Temperature Effects on Droplet Oscillation Decay with Application to Fuel Property Measurement

Observation of oscillation decay in droplets has been shown to be an effective approach in determining physical properties such as viscosity and surface tension for emerging biofuels using μl quantities. Herein this work extends the approach to higher temperatures relevant to fuel injection conditions for internal combustion engines. Experiments are conducted that use high-resolution strobed imaging of moving, heated, μm-sized, fuel droplets to capture shape oscillation decay through image processing and analysis. Two fuels are investigated, iso-butanol and a primary reference fuel (PRF 84), which is a mixture of iso-octane and n-heptane. A piezoelectric droplet generator is used to generate a continuous train of single droplets, which are given an initial perturbation and subsequently undergo damped oscillations, captured using strobed imaging. Surface tension and viscosity calculated at four different temperatures ranging from 30°C-55°C using the frequency and decay time associated with the fundamental mode are found to be within ~ 10% of reference values obtained from the literature. Complementary numerical simulations are performed that utilize a volume-of-fluid approach to track transient droplet oscillation phenomena along with heat and mass transfer in a 2D axisymmetric domain. Simulations, where droplet size and temperature can be independently varied, capture an expected decrease in oscillation frequency and increase in decay time, with increase in fuel temperature. The simulations are further used to study the relative contribution to deviations in surface tension and viscosity predictions due to heat and mass transfer from the droplet, as well as viscous effects violating the inviscid flow assumption in the droplet oscillation theory. Mass loss effects are found to be negligible. Temperature change due to heat transfer is found to have the next highest sensitivity, particularly for the more volatile PRF 84, which has a lower viscosity and associated Ohnesorge number. For isobutanol, which has a higher viscosity and Ohnesorge number, viscous effects contribute the most to deviation in fuel property predictions.

09 BIOMASS FUELS↗

DOE OSTI2016

Sky camera geometric calibration using solar observations

A camera model and associated automated calibration procedure for stationary daytime sky imaging cameras is presented. The specific modeling and calibration needs are motivated by remotely deployed cameras used to forecast solar power production where cameras point skyward and use 180° fisheye lenses. Sun position in the sky and on the image plane provides a simple and automated approach to calibration; special equipment or calibration patterns are not required. Sun position in the sky is modeled using a solar position algorithm (requiring latitude, longitude, altitude and time as inputs). Sun position on the image plane is detected using a simple image processing algorithm. The performance evaluation focuses on the calibration of a camera employing a fisheye lens with an equisolid angle projection, but the camera model is general enough to treat most fixed focal length, central, dioptric camera systems with a photo objective lens. Calibration errors scale with the noise level of the sun position measurement in the image plane, but the calibration is robust across a large range of noise in the sun position. In conclusion, calibration performance on clear days ranged from 0.94 to 1.24 pixels root mean square error.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

High-speed phase contrast imaging of spray breakup of jet fuels under combusting conditions

X-ray phase contrast imaging is conducted at 90,517 Hz on a fuel spray to characterize the breakup of the bulk fuel into ligaments and individual droplets in a single-sector, swirl-stabilized combustor under reacting conditions. Phase contrast imaging is used to qualitatively assess spray breakup for two fuels: Jet-A, which represents a normal viscosity fuel, and a blend of JP-5 (64%) and farnesane (36% by volume), which represents a high-viscosity fuel, at three fuel-flow rates and two air inlet temperatures. Time-series images of the fuels show that atomization occurs much more rapidly at higher fuel pressure with thinner ligaments being rapidly shredded. The high-viscosity fuel is qualitatively observed to have markedly longer, thicker ligaments and larger droplet diameters after the primary breakup than the normal viscosity fuel. Using an image processing and droplet quantification strategy, the mean droplet velocity magnitudes were found to decrease with decreasing fuel pressure and fuel-flow rate. The increase in preheat temperature from 323 to 370 K results in an increase in the mean droplet velocity magnitude and a decrease in numerical average and Sauter mean diameter, indicating improved atomization. The high-viscosity fuel was found to have larger average droplet diameters at each condition than the normal viscosity fuel. The increased preheat is found to enhance the combustion efficiency, which is hypothesized to couple with the improved atomization due to the higher combustion temperatures. This indicates the importance of examining spray atomization and breakup under realistic combusting conditions for relevant fuels as the heat release directly couples with the atomization process.

42 ENGINEERING↗

DOE OSTI2024

Random projection using random quantum circuits

The random sampling task performed by Google's Sycamore processor gave us a glimpse of the “quantum supremacy era.” This has definitely shed some light on the power of random quantum circuits in this abstract task of sampling outputs from the (pseudo)random circuits. In this paper, we explore a practical near-term use of local random quantum circuits in dimensional reduction of large low-rank data sets. We make use of the well-studied dimensionality reduction technique called the random projection method. This method has been extensively used in various applications such as image processing, logistic regression, entropy computation of low-rank matrices, etc. We prove that the matrix representations of local random quantum circuits with sufficiently shorter depths [ ∼ O ( n ) ] serve as good candidates for random projection. We demonstrate numerically that their projection abilities are not far off from the computationally expensive classical principal components analysis on MNIST and CIFAR-100 image datasets. We also benchmark the performance of quantum random projection against the commonly used classical random projection in the tasks of dimensionality reduction of image data sets and computing von Neumann entropies of large low-rank density matrices. And finally, using variational quantum singular value decomposition, we demonstrate a near-term implementation of extracting the singular vectors with dominant singular values after quantum random projecting a large low-rank matrix to lower dimensions. All such numerical experiments unequivocally demonstrate the ability of local random circuits to randomize a large Hilbert space at sufficiently shorter depths with robust retention of properties of large data sets in reduced dimensions. Published by the American Physical Society 2024

Kumaran, Keerthi (ORCID:0009000949125721)↗

DOE OSTI2019

Application of a convolutional neural network in permeability prediction: A case study in the Jacksonburg-Stringtown oil field, West Virginia, USA

Permeability is a critical parameter for understanding subsurface fluid flow behavior, managing reservoirs, enhancing hydrocarbon recovery, and sequestering carbon dioxide. In general, permeability is measured in the laboratory based on subsurface core samples, calculated from well logs or estimated from well tests. However, laboratory measurements and well tests are expensive, time-consuming, and usually limited to a few core samples or wells in a hydrocarbon field or carbon storage site. Machine-learning techniques are good options for generating a rapid, robust, and cost-effective permeability prediction model because of their strengths to recognize the potential interrelationships between input and output variables. Convolutional neural networks (CNN), as a good pattern recognition algorithm, are widely used in image processing, natural language processing, and speech recognition, but are rarely used with regression problems and even less often in reservoir characterization. We have developed a CNN regression model to estimate the permeability in the Jacksonburg-Stringtown oil field, West Virginia, which is a potential carbon storage site and enhanced oil recovery operations field. We also evaluate the concept of the geologic feature image, which is converted from geophysical well logs. Five variables, including two commonly available conventional well logs (the gamma rays [GRs] and bulk density) and three well-log-derived variables (the slopes of the GR and bulk density curves, and shale content), are used to generate a geologic feature image. The CNN treats the geologic feature image as the input and the permeability as the desired output. In addition, the permeability predicted using traditional backpropagation artificial neural networks, which are optimized by genetic algorithms and particle swarm optimization, is compared with the permeability estimated using our CNN. Our results indicate that the CNN regression model provides more accurate permeability predictions than the traditional neural network.

Geochemistry & Geophysics↗

DOE OSTI2025

Searching for Phase Transitions in Artificial Kagome Spin Ice

Artificial Kagome spin ice is a metasurface consisting of small islands of polarizable magnets. These islands can be oriented by an external magnetic field applied in the same plane as the metasurface. By subsequently applying a relatively weaker field in the opposite direction of the initial field, a portion of the magnets in the lattice can be repolarized or “flipped” the other way. These flips cause instabilities in a previously uniformly aligned lattice, causing the system to interact with itself and induce changes in the overall magnetization of the metasurface. This Summer, my goal was to use this phenomenon to discern whether or not these systems could undergo a phase transition caused only by the initial change of the external magnetic field. Based on previous datasets that indicated that such a transition was observable, my task was to find and reproduce this potential phenomena. This process was conducted by repeating measurements on the system by using an external magnet to align the spin ice and then using Magnetic Force Microscopy (MFM) to probe the surface of the material to understand the changes in the magnetization over time. This report will discuss the characteristics of artificial Kagome spin ice, the methodology used to induce phase transitions, and the image processing methods used to understand the results. Although no reproducible evidence of a phase transition was found during the Summer, we were able to successfully reproduce short-term responses in the spin ice, as well as plot a hysteresis curve of the material.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2012

The relationship between anatomic noise and volumetric breast density for digital mammography

Purpose: The appearance of parenchymal/stromal patterns in mammography have been characterized as having a Wiener power spectrum with an inverse power-law shape described by the exponential parameter, {beta}. The amount of fibroglandular tissue, which can be quantified in terms of volumetric breast density (VBD), influences the texture and appearance of the patterns formed in a mammogram. Here, a large study is performed to investigate the variations in {beta} in a clinical population and to indicate the relationship between {beta} and breast density. Methods: From a set of 2686 cranio-caudal normal screening mammograms, the parameter {beta} was extracted from log-log fits to the Wiener spectrum over the range 0.15-1 mm{sup -1}. The Wiener spectrum was calculated from regions of interest in the compression paddle contact region of the breast. An in-house computer program, Cumulus V, was used to extract the volumetric breast density and identify the compression paddle contact regions of the breast. The Wiener spectra were calculated with and without modulation transfer function (MTF) correction to determine the impact of VBD on the intrinsic anatomic noise. Results: The mean volumetric breast density was 25.5% ({+-}12.6%) over all images. The mean {beta} following a MTF correction which decreased the {beta} slightly ( Almost-Equal-To -0.08) was found to be 2.87. Varying the maximum of the spatial frequency range of the fits from 0.7 to 1.0, 1.25 or 1.5 mm{sup -1} showing small decreases in the result, although the effect of the quantum noise power component on reducing {beta} was clearly observed at 1.5 mm{sup -1}. Conclusions: The texture parameter, {beta}, was found to increase with VBD at low volumetric breast densities with an apparent leveling off at higher densities. The relationship between {beta} and VBD measured here can be used to create probabilistic models for computer simulations of detectability. As breast density is a known risk predictor for breast cancer, the correlation between {beta} and VBD suggests that {beta} may provide predictive information and this will be investigated in the future.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2013

Toward in vivo lung's tissue incompressibility characterization for tumor motion modeling in radiation therapy

Purpose: A novel technique is proposed to characterize lung tissue incompressibility variation during respiration. Estimating lung tissue incompressibility parameter variations resulting from air content variation throughout respiration is critical for computer assisted tumor motion tracking. Continuous tumor motion is a major challenge in lung cancer radiotherapy, especially with external beam radiotherapy. If not accounted for, this motion may lead to areas of radiation overdosage for normal tissue. Given the unavailability of imaging modality that can be used effectively for real-time lung tumor tracking, computer assisted approach based on tissue deformation estimation can be a good alternative. This approach involves lung biomechanical model where its fidelity depends on input tissue properties. This investigation shows that considering variable tissue incompressibility parameter is very important for predicting tumor motion accurately, hence improving the lung radiotherapy outcome. Methods: First, an in silico lung phantom study was conducted to demonstrate the importance of employing variable Poisson's ratio for tumor motion predication. After it was established that modeling this variability is critical for accurate tumor motion prediction, an optimization based technique was developed to estimate lung tissue Poisson's ratio as a function of respiration cycle time. In this technique, the Poisson's ratio and lung pressure value were varied systematically until optimal values were obtained, leading to maximum similarity between acquired and simulated 4D CT lung images. This technique was applied in an ex vivo porcine lung study where simulated images were constructed using the end exhale CT image and deformation fields obtained from the lung's FE modeling of each respiration time increment. To model the tissue, linear elastic and Marlow hyperelastic material models in conjunction with variable Poisson's ratio were used. Results: The phantom study showed that the tumor motion trajectory and its final locations obtained from simulations with and without considering tissue incompressibility variation were very different. For example, tumor displacements in the z direction were -11.23 and -38.10 mm obtained with the Marlow hyperelastic material model in conjunction with constant and variable Poisson's ratio, respectively. By comparing the acquired 4D-CT image sequence of the porcine lung with their image sequence counterparts obtained from the hyperelastic model with constant and variable Poisson's ratio, it was shown that using variable tissue incompressibility reduced errors significantly in tumor motion prediction. Conclusions: This investigation demonstrates the importance of incompressibility variation estimation and utilization for accurate tumor tracking in computer assisted lung external beam radiation therapy. An optimization framework was developed to estimate a Poisson's ratio function in terms of respiration cycle time using experimental image data of the lung. Utilizing this function along with respiratory system FE modeling may lead to more effective tumor targeting, hence potentially improving the outcome of lung external beam radiation therapy techniques. This is particularly true for stereotactic body radiation therapy where only one or a few fraction treatments are applied, precluding the possibility of averaging out dosimetric deviations introduced by the respiratory motion.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Review of High‐Speed Digital Image Correlation: Advancements and Good Practices

This paper reviews the current state of the art in high‐speed (HS) and ultrahigh‐speed (UHS) digital image correlation (DIC) techniques, emphasizing their critical role in experimental research across various scientific domains. HS and UHS DIC have evolved significantly, driven by advancements in camera systems, image processing algorithms and experimental methodologies. These developments have opened new avenues for capturing and analysing dynamic events with unprecedented temporal and spatial detail, but not without introducing challenges such as optical distortions, motion blur and lighting issues that can affect measurement quality. This review advocates for standardized reporting practices in HS/UHS DIC methodologies to improve reproducibility and reliability across studies, drawing on guidelines from the International Digital Image Correlation Society (iDICs). Through a comprehensive analysis of over 150 articles, this review identifies key advancements in imaging technology and their application in six research domains: material characterization, test development, fracture mechanics, model validation, ballistic and explosive phenomena assessment and measurement uncertainties. Distinctions between two‐dimensional (2D) and stereo‐DIC applications are explored, offering insights into their practical implementation and trade‐offs. Good practices for HS/UHS DIC applications are proposed along with suggestions for future directions for this evolving field, highlighting the indispensable role of technological innovation in expanding the capabilities of optical metrology.

experimental mechanics↗

DOE OSTI2021

Evolution of standardization and dissemination of cryo-EM structures and data jointly by the community, PDB, and EMDB

Cryogenic electron microscopy (cryo-EM) methods began to be used in the mid-1970s to study thin and periodic arrays of proteins. Following a half-century of development in cryo-specimen preparation, instrumentation, data collection, data processing and modeling software, cryo-EM has become a routine method for solving structures from large biological assemblies to small biomolecules at near to true atomic resolution. This review explores the critical roles played by the Protein Data Bank (PDB) and Electron Microscopy Data Bank (EMDB) in partnership with the community to develop the necessary infrastructure to archive cryo-EM maps and associated models. Public access to cryo-EM structure data has in turn facilitated better understanding of structure-function relationships and advancement of image processing and modeling tool development. The partnership between the global cryo-EM community and PDB and EMDB leadership has synergistically shaped the standards for metadata, one-stop deposition of maps and models, and validation metrics to assess the quality of cryo-EM structures. The advent of cryo-electron tomography (cryo-ET) for in situ molecular cell structures at a broad resolution range and their correlations with other imaging data introduces new data archival challenges in terms of data size and complexity in the years to come.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2013

LONG-TERM MONITORING OF COMET 103P/HARTLEY 2

We report the spectrophotometric, photometric, and imaging monitoring results of comet 103P/Hartley 2 obtained at the Lulin (1 m), Calar Alto (2.2 m), and Beijing Astronomical (2.16 m) observatories from 2010 April to December. We found that a dust feature in the sunward direction was detected starting from the end of September until the beginning of December (our last observation from the Lulin and Calar Alto observatories). Two distinct sunward jet features in the processed images were observed on October 11 and after October 29 until November 2. In parallel, the CN images reveal two asymmetrical jet features which are nearly perpendicular to the Sun-nucleus direction, these asymmetrical features imply that the comet was in a nearly side-on view in late October and early November. In addition to the jet features, the average result of the C{sub 2}-to-CN production rate ratio ranges from 0.7 to 1.5, consistent with 103P/Hartley 2 being of typical cometary chemistry. We found that the r{sub h} dependence for the dust production rate, Af{rho} (5000 km), is -3.75 {+-} 0.45 before perihelion and -3.44 {+-} 1.20 during the post-perihelion period. We detected higher dust reddening around the optocenter and decreased reddening along the sunward jet feature. We concluded that higher dust reddening could be associated with strong jet activity while lower dust reddening could be associated with the outburst or might imply changes in the optical properties. The average dust color did not appear to vary significantly as the comet passed through perihelion.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Neutron Tomography at the Los Alamos Neutron Science Center

Neutron imaging is an incredibly powerful tool for non-destructive sample characterization and materials science. Neutron tomography is one technique that results in a three-dimensional model of the sample, representing the interaction of the neutrons with the sample. This relies both on reliable data acquisition and on image processing after acquisition. Over the course of the project, the focus has changed from the former to the latter, culminating in a large-scale reconstruction of a meter-long fossilized skull. The full reconstruction is not yet complete, though tools have been developed to improve the speed and accuracy of the reconstruction. This project helps to improve the capabilities of LANSCE and LANL with regards to imaging large or unwieldy objects.

36 MATERIALS SCIENCE↗