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Enabling Particulate Materials Processing Science for High-Consequence, Small-Lot Precision Manufacturing

This Laboratory Directed Research and Development project developed and applied closely coupled experimental and computational tools to investigate powder compaction across multiple length scales. The primary motivation for this work is to provide connections between powder feedstock characteristics, processing conditions, and powder pellet properties in the context of powder-based energetic components manufacturing. We have focused our efforts on multicrystalline cellulose, a molecular crystalline surrogate material that is mechanically similar to several energetic materials of interest, but provides several advantages for fundamental investigations. We report extensive experimental characterization ranging in length scale from nanometers to macroscopic, bulk behavior. Experiments included nanoindentation of well-controlled, micron-scale pillar geometries milled into the surface of individual particles, single-particle crushing experiments, in-situ optical and computed tomography imaging of the compaction of multiple particles in different geometries, and bulk powder compaction. In order to capture the large plastic deformation and fracture of particles in computational models, we have advanced two distinct meshfree Lagrangian simulation techniques: 1.) bonded particle methods, which extend existing discrete element method capabilities in the Sandia-developed , open-source LAMMPS code to capture particle deformation and fracture and 2.) extensions of peridynamics for application to mesoscale powder compaction, including a novel material model that includes plasticity and creep. We have demonstrated both methods for simulations of single-particle crushing as well as mesoscale multi-particle compaction, with favorable comparisons to experimental data. We have used small-scale, mechanical characterization data to inform material models, and in-situ imaging of mesoscale particle structures to provide initial conditions for simulations. Both mesostructure porosity characteristics and overall stress-strain behavior were found to be in good agreement between simulations and experiments. We have thus demonstrated a novel multi-scale, closely coupled experimental and computational approach to the study of powder compaction. This enables a wide range of possible investigations into feedstock-process-structure relationships in powder-based materials, with immediate applications in energetic component manufacturing, as well as other particle-based components and processes.

36 MATERIALS SCIENCE↗

SU-F-T-115: Uncertainty in the Esophagus Dose in Retrospective Epidemiological Study of Breast Cancer Radiotherapy Patients

Purpose: Epidemiological studies of second cancer risks in breast cancer radiotherapy patients often use generic patient anatomy to reconstruct normal tissue doses when CT images of patients are not available. To evaluate the uncertainty involved in the dosimetry approach, we evaluated the esophagus dose in five sample patients by simulating breast cancer treatments. Methods: We obtained the diagnostic CT images of five anonymized adult female patients in different Body Mass Index (BMI) categories (16– 36kg/m2) from National Institutes of Health Clinical Center. We contoured the esophagus on the CT images and imported them into a Treatment Planning System (TPS) to create treatment plans and calculate esophagus doses. Esophagus dose was calculated once again via experimentally-validated Monte Carlo (MC) transport code, XVMC under the same geometries. We compared the esophagus doses from TPS and the MC method. We also investigated the degree of variation in the esophagus dose across the five patients and also the relationship between the patient characteristics and the esophagus doses. Results: Eclipse TPS using Analytical Anisotropic Algorithm (AAA) significantly underestimates the esophagus dose in breast cancer radiotherapy compared to MC. In the worst case, the esophagus dose from AAA was only 40% of the MC dose. The Coefficient of Variation across the patients was 48%. We found that the maximum esophagus dose was up to 2.7 times greater than the minimum. We finally observed linear relationship (Dose = 0.0218 × BMI – 0.1, R2=0.54) between patient’s BMI and the esophagus doses. Conclusion: We quantified the degree of uncertainty in the esophagus dose in five sample breast radiotherapy patients. The results of the study underscore the importance of individualized dose reconstruction for the study cohort to avoid misclassification in the risk analysis of second cancer. We are currently extending the number of patients up to 30.

60 APPLIED LIFE SCIENCES↗

Complete set of detectors for studying cosmic gamma-ray bursts onboard the Lomonosov satellite

The scientific instruments onboard the Lomonosov satellite include a complete set of detectors designed to study the gamma and optical emission of cosmic gamma-ray bursts (GRBs). The BDRG gamma spectrometer ensures producing a trigger of a GRB and studying GRB properties in the energy range of 10–3000 keV as well as determining the GRB source coordinates by comparing readings of three differently directed detectors. The SHOK optical cameras (with a field of view of ~20 × 40 degrees) fix a set of images by the GRB trigger preceding the trigger and a post-trigger set at a frequency of about five frames per second. The UFFO instrument incorporates the UBAT telescope with a coding mask for measurements within a range of hard X rays and soft gamma rays and the SMT optical slewing mirror telescope, which can be directed at the GRB source in about 1 s to measure the GRB optical emission at early stages.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

XPlacer/Tracer

XPlacer/Tracer is a dynamic analysis tool that finds bad memory access patterns in heterogeneous codes. XPlacer/Tracer consists of two components. (1) A configurable ROSE plugin for source code instrumentation of heterogeneous code written in the C/C++ and CUDA programming languages. (2) A sample configuration that instruments memory accesses to dynamic memory in CPU and GPU codes, and a runtime library that tracks these memory accesses at runtime. The collected information is reported in form of a textual summary or as memory map that can be converted to images.

Pirkelbauer, PeterM.↗

Analysis and Distribution of Proppant Recovered from Fracture Faces in the HFTS Slant Core Drilled through a Stimulated Reservoir

Although sand proppant has been used since 1949 to increase efficacy of hydraulically fractured treatments by preventing fractures from closing after well depressurization, many questions remain regarding the behavior and distribution of proppant in the subsurface. To this end, we quantified the amount of recovered proppant in open fractures within a slant core drilled through hydraulically fractured Wolfcamp Shale. To improve understanding of hydraulic-fracture growth and patterns, we then addressed basic questions such as the following regarding proppant behavior in the subsurface: Is there variation along the length of the examined core? Is the proppant mainly found in hydraulic fractures, in reactivated natural fractures, or is it transported into drilling-induced fractures during recovery? Do the majority of proppant grains remain whole or tend to get crushed? To answer these questions, we collected all material from every open fracture (407 samples total) within ~600 ft of core. Samples consisted of drilling mud, aluminum shavings from the core barrel, shale and lithic fragments, calcite, and, potentially, sand proppant (95% plain and 5% colored resin-coated grains) pumped during the hydraulic fracturing of adjacent wells. We then washed, sieved into four size fractions, weighed, and imaged all samples for quantitative image analysis. Retrieved samples were labeled with respect to a master fracture database, where fractures were identified in the core and on CT scans of each 3-ft interval, allowing us to code them as either hydraulic, natural reactivated, or drilling/recovery-induced fractures. From this coding, we quantified the amount of proppant within each fracture, analyzed the distribution of grains among different fracture types, and traced base versus colored grains. Proppant packs 0.5–1 cm thick were found in two locations where there was complex fracture geometry, but fracture faces showed no evidence of proppant embedment. In situ sand patches were found on a few fracture faces, mostly in fractures near the proppant packs. Pumped proppant was 100 and 40/70 mesh (149–420 μm), and even though widespread grain crushing is not observed, the majority of recovered proppant ranges from 63 to 250 μm. The distribution of retrieved proppant, especially the larger retrieved sizes (250– >500 μm), mirrors the proximity of the slant core to the hydraulic fracture treatment wells. Hydraulic fracture samples contained variable amounts of proppant, and natural reactivated fractures sometimes contained more proppant than nearby hydraulic fractures, suggesting transference between fracture types in the subsurface. Regarding colored proppant, some colored sands occurred in discreet fractures, whereas other colors appeared to be mixed and widespread. Ultimately, all fractures contain at least some proppant, especially in the smallest size fractions; however, the extent to which the proppant was introduced during the core-drilling process is still unknown. Our study is one of the first attempts at physically recovering and quantifying injected proppant from parted fracture breaks within a stimulated reservoir, and the results are significant in terms of understanding propped fracture networks and predicting future proppant distribution during hydraulic fracturing.

Elliott, Sara↗

Investigation on the Core Bypass Flow in a Very High Temperature Reactor

Uncertainties associated with the core bypass flow are some of the key issues that directly influence the coolant mass flow distribution and magnitude, and thus the operational core temperature profiles, in the very high-temperature reactor (VHTR). Designers will attempt to configure the core geometry so the core cooling flow rate magnitude and distribution conform to the design values. The objective of this project is to study the bypass flow both experimentally and computationally. Researchers will develop experimental data using state-of-the-art particle image velocimetry in a small test facility. The team will attempt to obtain full field temperature distribution using racks of thermocouples. The experimental data are intended to benchmark computational fluid dynamics (CFD) codes by providing detailed information. These experimental data are urgently needed for validation of the CFD codes. The following are the project tasks: (1) Construct a small-scale bench-top experiment to resemble the bypass flow between the graphite blocks, varying parameters to address their impact on bypass flow. Wall roughness of the graphite block walls, spacing between the blocks, and temperature of the blocks are some of the parameters to be tested. (2) Perform CFD to evaluate pre- and post-test calculations and turbulence models, including sensitivity studies to achieve high accuracy. (3) Develop the state-of-the art large eddy simulation (LES) using appropriate subgrid modeling. (4) Develop models to be used in systems thermal hydraulics codes to account and estimate the bypass flows. These computer programs include, among others, RELAP3D, MELCOR, GAMMA, and GAS-NET. Actual core bypass flow rate may vary considerably from the design value. Although the uncertainty of the bypass flow rate is not known, some sources have stated that the bypass flow rates in the Fort St. Vrain reactor were between 8 and 25 percent of the total reactor mass flow rate. If bypass flow rates are on the high side, the quantity of cooling flow through the core may be considerably less than the nominal design value, causing some regions of the core to operate at temperatures in excess of the design values. These effects are postulated to lead to localized hot regions in the core that must be considered when evaluating the VHTR operational and accident scenarios.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Final Technical Report for "Applied Mathematics Research: Simulation Based Optimization and Application to Electromagnetic Inverse Problems"

The focus of research was: Developing adaptive mesh for the solution of Maxwell's equations; Developing a parallel framework for time dependent inverse Maxwell's equations; Developing multilevel methods for optimization problems with inequality constraints; A new inversion code for inverse Maxwell's equations in the 0th frequency (DC resistivity); A new inversion code for inverse Maxwell's equations in low frequency regime. Although the research concentrated on electromagnetic forward and in- verse problems the results of the research was applied to the problem of image registration.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A library of MiMICs allows tagging of genes and reversible, spatial and temporal knockdown of proteins in Drosophila

Here, we document a collection of ~7434 MiMIC (Minos Mediated Integration Cassette) insertions of which 2854 are inserted in coding introns. They allowed us to create a library of 400 GFP-tagged genes. We show that 72% of internally tagged proteins are functional, and that more than 90% can be imaged in unfixed tissues. Moreover, the tagged mRNAs can be knocked down by RNAi against GFP (iGFPi), and the tagged proteins can be efficiently knocked down by deGradFP technology. The phenotypes associated with RNA and protein knockdown typically correspond to severe loss of function or null mutant phenotypes. Finally, we demonstrate reversible, spatial, and temporal knockdown of tagged proteins in larvae and adult flies. This new strategy and collection of strains allows unprecedented in vivo manipulations in flies for many genes. These strategies will likely extend to vertebrates.

Nagarkar-Jaiswal, Sonal↗

Optimal Matched Filter in the Low-number Count Poisson Noise Regime and Implications for X-Ray Source Detection

Detection of templates (e.g., sources) embedded in low-number count Poisson noise is a common problem in astrophysics. Examples include source detection in X-ray images, γ-rays, UV, neutrinos, and search for clusters of galaxies and stellar streams. However, the solutions in the X-ray-related literature are sub-optimal in some cases by considerable factors. Using the lemma of Neyman–Pearson, we derive the optimal statistics for template detection in the presence of Poisson noise. We demonstrate that, for known template shape (e.g., point sources), this method provides higher completeness, for a fixed false-alarm probability value, compared with filtering the image with the point-spread function (PSF). In turn, we find that filtering by the PSF is better than filtering the image using the Mexican-hat wavelet (used by wavdetect). For some background levels, our method improves the sensitivity of source detection by more than a factor of two over the popular Mexican-hat wavelet filtering. This filtering technique can also be used for fast PSF photometry and flare detection; it is efficient and straightforward to implement. We provide an implementation in MATLAB. The development of a complete code that works on real data, including the complexities of background subtraction and PSF variations, is deferred for future publication.

79 ASTRONOMY AND ASTROPHYSICS↗

SU-D-207-07: Implementation of Full/half Bowtie Filter Model in a Commercial Treatment Planning System for Kilovoltage X-Ray Imaging Dose Estimation

Purpose: To implement full/half bowtie filter models in a commercial treatment planning system (TPS) to calculate kilovoltage (kV) x-ray imaging dose of Varian On-Board Imager (OBI) cone beam CT (CBCT) system. Methods: Full/half bowtie filters of Varian OBI were created as compensator models in Pinnacle TPS (version 9.6) using Matlab software (version 2011a). The profiles of both bowtie filters were acquired from the manufacturer, imported into the Matlab system and hard coded in binary file format. A Pinnacle script was written to import each bowtie filter data into a Pinnacle treatment plan as a compensator. A kV x-ray beam model without including the compensator model was commissioned per each bowtie filter setting based on percent depth dose and lateral profile data acquired from Monte Carlo simulations. To validate the bowtie filter models, a rectangular water phantom was generated in the planning system and an anterior/posterior beam with each bowtie filter was created. Using the Pinnacle script, each bowtie filter compensator was added to the treatment plan. Lateral profile at the depth of 3cm and percent depth dose were measured using an ion chamber and compared with the data extracted from the treatment plans. Results: The kV x-ray beams for both full and half bowtie filter have been modeled in a commercial TPS. The difference of lateral and depth dose profiles between dose calculations and ion chamber measurements were within 6%. Conclusion: Both full/half bowtie filter models provide reasonable results in kV x-ray dose calculations in the water phantom. This study demonstrates the possibility of using a model-based treatment planning system to calculate the kV imaging dose for both full and half bowtie filter modes. Further study is to be performed to evaluate the models in clinical situations.

60 APPLIED LIFE SCIENCES↗

Image-based spectral distortion correction for photon-counting x-ray detectors

Purpose: To investigate the feasibility of using an image-based method to correct for distortions induced by various artifacts in the x-ray spectrum recorded with photon-counting detectors for their application in breast computed tomography (CT). Methods: The polyenergetic incident spectrum was simulated with the tungsten anode spectral model using the interpolating polynomials (TASMIP) code and carefully calibrated to match the x-ray tube in this study. Experiments were performed on a Cadmium-Zinc-Telluride (CZT) photon-counting detector with five energy thresholds. Energy bins were adjusted to evenly distribute the recorded counts above the noise floor. BR12 phantoms of various thicknesses were used for calibration. A nonlinear function was selected to fit the count correlation between the simulated and the measured spectra in the calibration process. To evaluate the proposed spectral distortion correction method, an empirical fitting derived from the calibration process was applied on the raw images recorded for polymethyl methacrylate (PMMA) phantoms of 8.7, 48.8, and 100.0 mm. Both the corrected counts and the effective attenuation coefficient were compared to the simulated values for each of the five energy bins. The feasibility of applying the proposed method to quantitative material decomposition was tested using a dual-energy imaging technique with a three-material phantom that consisted of water, lipid, and protein. The performance of the spectral distortion correction method was quantified using the relative root-mean-square (RMS) error with respect to the expected values from simulations or areal analysis of the decomposition phantom. Results: The implementation of the proposed method reduced the relative RMS error of the output counts in the five energy bins with respect to the simulated incident counts from 23.0%, 33.0%, and 54.0% to 1.2%, 1.8%, and 7.7% for 8.7, 48.8, and 100.0 mm PMMA phantoms, respectively. The accuracy of the effective attenuation coefficient of PMMA estimate was also improved with the proposed spectral distortion correction. Finally, the relative RMS error of water, lipid, and protein decompositions in dual-energy imaging was significantly reduced from 53.4% to 6.8% after correction was applied. Conclusions: The study demonstrated that dramatic distortions in the recorded raw image yielded from a photon-counting detector could be expected, which presents great challenges for applying the quantitative material decomposition method in spectral CT. The proposed semi-empirical correction method can effectively reduce these errors caused by various artifacts, including pulse pileup and charge sharing effects. Furthermore, rather than detector-specific simulation packages, the method requires a relatively simple calibration process and knowledge about the incident spectrum. Therefore, it may be used as a generalized procedure for the spectral distortion correction of different photon-counting detectors in clinical breast CT systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Processing of Ice Cloud In Situ Data Collected by Bulk Water, Scattering, and Imaging Probes: Fundamentals, Uncertainties, and Efforts toward Consistency

Abstract In situ observations of cloud properties made by airborne probes play a critical role in ice cloud research through their role in process studies, parameterization development, and evaluation of simulations and remote sensing retrievals. To determine how cloud properties vary with environmental conditions, in situ data collected during different field projects processed by different groups must be used. However, because of the diverse algorithms and codes that are used to process measurements, it can be challenging to compare the results. Therefore it is vital to understand both the limitations of specific probes and uncertainties introduced by processing algorithms. Since there is currently no universally accepted framework regarding how in situ measurements should be processed, there is a need for a general reference that describes the most commonly applied algorithms along with their strengths and weaknesses. Methods used to process data from bulk water probes, single-particle light-scattering spectrometers and cloud-imaging probes are reviewed herein, with emphasis on measurements of the ice phase. Particular attention is paid to how uncertainties, caveats, and assumptions in processing algorithms affect derived products since there is currently no consensus on the optimal way of analyzing data. Recommendations for improving the analysis and interpretation of in situ data include the following: establishment of a common reference library of individual processing algorithms, better documentation of assumptions used in these algorithms, development and maintenance of sustainable community software for processing in situ observations, and more studies that compare different algorithms with the same benchmark datasets.

54 ENVIRONMENTAL SCIENCES↗

Compressive Classification for TEM-EELS

Acquiring atomic-resolution images of beam sensitive materials or under dynamic conditions (e.g. operando STEM) is very difficult and requires precise dose fractioning to minimize the dose delivered to the sample and acquire the data more rapidly than dynamics present. Typical methods of low-dose STEM imaging include adjusting the beam current, dwell-time, and probe Scanning transmission electron microscopy (STEM) is used routinely to obtain atomic-resolution images of a small selection of radiation tolerant materials under stable conditions.size. All three of these determine the dose over a spatial area in STEM. Recently, compressive sensing [1] has been applied to electron microscopy. The computational imaging method of inpainting [2] has been proposed as a method to reduce dose and increase acquisition speed for STEM. Inpainting is a technique to recover missing pixels in an image. By skipping pixels (randomly) during acquisition, a fourth dose-control mechanism is realized [3]. A few implementations of randomly-subsampled STEM exist (e.g., [4]). To make the concepts of compressive sensing accessible to the microscopy community we begin with an example using atomic resolution images of a GaAs crystal (see Figure 1). Because the crystal is periodic it has a sparse representation in reciprocal space. In fact, a sparse representation is a key component of compressive sensing. If an image is sub-sampled randomly we find that the Fourier transform remains sparse, but becomes increasing noisy as less and less data is acquired. Yet, by finding the peaks in the reciprocal image and removing the noise it is possible to recover atomic resolution images with only 1% of the pixels. Figure 1 shows the reconstruction process for GaAs sub-sampled at 50%, 10%, 5%, and 1%. Periodic images form a special class for which the optimal sampling approach (according to CS theory) is a random selection of pixels. For non-periodic images, such as those arising in in-situ STEM, methods such as dictionary learning are necessary [2,5]. The data can be compressed in time for TEM [5] or pixels can be skipped randomly for STEM. There are several issues that arise in developing a random scan for STEM [4] and a coded aperture for TEM. The remainder of the talk will address these issues. References: [1] E Candes and M Wakin. Signal Processing Magazine, IEEE. 2(25) (2008), pp. 21. [2] A Stevens, Pu Y, Sun Y, et al. Artificial Intelligence & Statistics (AISTATS), 2017. [3] A Stevens, H Yang, L Carin et al. Microscopy 63(1), (2014), pp. 41. [4] L Kovarik, A Stevens, A Liyu et al. Appl. Phys. Lett. 109, 164102 (2016). [5] A Stevens, L Kovarik, P Abellan et al. Adv. Structural and Chemical Imaging 1(10), (2015), pp. 1. [6] Supported by the Chemical Imaging, Signature Discovery, and Analytics in Motion Initiatives at PNNL. PNNL is operated by Battelle Memorial Inst. for the US DOE; contract DE-AC05-76RL01830.

Hao, Weituo↗

Development of a compact E ? B microchannel plate detector for beam imaging

A beam imaging detector was developed by coupling a multi-strip anode with delay line readout to an E×B microchannel plate (MCP) detector. This detector is capable of measuring the incident position of the beam particles in one-dimension. To assess the spatial resolution, the detector was illuminated by an α-source with an intervening mask that consists of a series of precisely-machined slits. The measured spatial resolution was 520 um source FWHM, which was improved to 413 um FWHM by performing an FFT of the signals, rejecting spurious signals on the delay line, and requiring a minimum signal amplitude. This measured spatial resolution of 413 um FWHM corresponds to an intrinsic resolution of 334 um FWHM when the effect of the finite slit width is de-convoluted. To understand the measured resolution, the performance of the detector is simulated with the ion-trajectory code SIMION.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Concomitant Imaging Dose and Cancer Risk in Image Guided Thoracic Radiation Therapy

Purpose: Kilovoltage cone beam computed tomography (CT) (kVCBCT) imaging guidance improves the accuracy of radiation therapy but imposes an extra radiation dose to cancer patients. This study aimed to investigate concomitant imaging dose and associated cancer risk in image guided thoracic radiation therapy. Methods and Materials: The planning CT images and structure sets of 72 patients were converted to CT phantoms whose chest circumferences (C{sub chest}) were calculated retrospectively. A low-dose thorax protocol on a Varian kVCBCT scanner was simulated by a validated Monte Carlo code. Computed doses to organs and cardiac substructures (for 5 selected patients of various dimensions) were regressed as empirical functions of C{sub chest}, and associated cancer risk was calculated using the published models. The exposures to nonthoracic organs in children were also investigated. Results: The structural mean doses decreased monotonically with increasing C{sub chest}. For all 72 patients, the median doses to the heart, spinal cord, breasts, lungs, and involved chest were 1.68, 1.33, 1.64, 1.62, and 1.58 cGy/scan, respectively. Nonthoracic organs in children received 0.6 to 2.8 cGy/scan if they were directly irradiated. The mean doses to the descending aorta (1.43 ± 0.68 cGy), left atrium (1.55 ± 0.75 cGy), left ventricle (1.68 ± 0.81 cGy), and right ventricle (1.85 ± 0.84 cGy) were significantly different (P<.05) from the heart mean dose (1.73 ± 0.82 cGy). The blade shielding alleviated the exposure to nonthoracic organs in children by an order of magnitude. Conclusions: As functions of patient size, a series of models for personalized estimation of kVCBCT doses to thoracic organs and cardiac substructures have been proposed. Pediatric patients received much higher doses than did the adults, and some nonthoracic organs could be irradiated unexpectedly by the default scanning protocol. Increased cancer risks and disease adverse events in the thorax were strongly related to higher imaging doses and smaller chest dimensions.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Monte Carlo N-Particle forward modeling for density reconstruction of double shell capsule radiographs

In the Double Shell Inertial Confinement Fusion concept, characterizing the shape asymmetry of imploding metal shells is vital for understanding energy-efficient compression and radiative losses of the thermonuclear fuel. The Monte Carlo N-Particle MCNP® code forward models radiography of Double Shell capsule implosions using the Advanced Radiographic Capability at the National Ignition Facility. A procedure is developed for using MCNP to reconstruct density profiles from the radiograph image intensity. For a given Double Shell imploding target geometry, MCNP radiographs predict image contrast, which can help guide experimental design. Finally, in future work, the calculated MCNP synthetic radiographs will be compared with experimental radiographs to determine the radial and azimuthal density profiles of the Double Shell capsules.

47 OTHER INSTRUMENTATION↗

Photometric redshifts from SDSS images with an interpretable deep capsule network

ABSTRACT Studies of cosmology, galaxy evolution, and astronomical transients with current and next-generation wide-field imaging surveys like the Rubin Observatory Legacy Survey of Space and Time are all critically dependent on estimates of photometric redshifts. Capsule networks are a new type of neural network architecture that is better suited for identifying morphological features of the input images than traditional convolutional neural networks. We use a deep capsule network trained on ugriz images, spectroscopic redshifts, and Galaxy Zoo spiral/elliptical classifications of ∼400 000 Sloan Digital Sky Survey galaxies to do photometric redshift estimation. We achieve a photometric redshift prediction accuracy and a fraction of catastrophic outliers that are comparable to or better than current methods for SDSS main galaxy sample-like data sets (r ≤ 17.8 and zspec ≤ 0.4) while requiring less data and fewer trainable parameters. Furthermore, the decision-making of our capsule network is much more easily interpretable as capsules act as a low-dimensional encoding of the image. When the capsules are projected on a two-dimensional manifold, they form a single redshift sequence with the fraction of spirals in a region exhibiting a gradient roughly perpendicular to the redshift sequence. We perturb encodings of real galaxy images in this low-dimensional space to create synthetic galaxy images that demonstrate the image properties (e.g. size, orientation, and surface brightness) encoded by each dimension. We also measure correlations between galaxy properties (e.g. magnitudes, colours, and stellar mass) and each capsule dimension. We publicly release our code, estimated redshifts, and additional catalogues at https://biprateep.github.io/encapZulate-1.

79 ASTRONOMY AND ASTROPHYSICS↗

MO-B-BRD-00: Clinical Applications of 3D Printing

This session is designed so that the learning objectives are practical. The intent is that the attendee may take home an understanding of not just the technology, but also the logistical steps necessary to execute these 3D printing techniques in the clinic. Four practical 3D printing topics will be discussed: (i) Creating bolus and compensators for photon machines; (ii) tools for proton therapy; (iii) clinical applications in imaging; (iv) custom phantom design for clinic and research use. The use of 3D printers within the radiation oncology setting is proving to be a useful tool for creating patient specific bolus and compensators with the added benefit of cost savings. Creating the proper protocol is essential to ensuring that the desired effect is achieved and modeled in the treatment planning system. The critical choice of printer material (since it determines the interaction with the radiation) will be discussed. Selection of 3D printer type, design methods, verification of dose calculation, and the printing process will be detailed to give the basis for establishing your own protocol for electron and photon fields. A practical discussion of likely obstacles that may be encountered will be included. The diversity of systems and techniques in proton facilities leads to different facilities having very different requirements for beam modifying hardware and quality assurance devices. Many departments find the need to design and fabricate facility-specific equipment, making 3D printing an attractive technology. 3D printer applications in proton therapy will be discussed, including beam filters and compensators, and the design of proton therapy specific quality assurance tools. Quality control specific to 3D printing in proton therapy will be addressed. Advantages and disadvantages of different printing technology for these applications will also be discussed. 3D printing applications using high-resolution radiology-based imaging data will be presented. This data is used to 3D print individualized physical models of patient’s unique anatomy for aid in planning complex and challenging surgical procedures. Methods, techniques and imaging requirements for 3D printing anatomic models from imaging data will be discussed. Specific applications currently being used in the radiology clinic will be detailed. Standardized phantoms for radiation therapy are abundant. However, custom phantom designs can be advantageous for both clinical tasks and research. 3D printing is a useful method of custom fabrication that allows one to construct custom objects relatively quickly. Possibilities for custom radiotherapy phantoms range from 3D printing a hollow shell and filling the shell with tissue equivalent materials to fully printing the entire phantom with materials that are tissue equivalent as well as suitable for 3D printing. A range of materials available for use in radiotherapy phantoms and in the case of phantoms for dosimetric measurements, this choice is critical. The necessary steps required will be discussed including: modalities of 3D model generation, 3D model requirements for 3D printing, generation of machine instructions from the 3D model, and 3D printing techniques, choice of phantoms material, and troubleshooting techniques for each step in the process. Case examples of 3D printed phantoms will be shown. Learning Objectives: Understand the types of 3D modeling software required to design your device, the file formats required for data transfer from design software to 3D printer, and general troubleshooting techniques for each step of the process. Learn the differences between materials and design for photons vs. electrons vs. protons. Understand the importance of material choice and design geometries for your custom phantoms. Learn specific steps of quality assurance and quality control for 3D printed beam filters and compensators for proton therapy. Learn of special 3D printing applications for imaging. Cunha: Research support from Phillips Healthcare.

60 APPLIED LIFE SCIENCES↗