Results for “Image coding” — Page 65

DOE OSTI2015

MO-B-BRD-02: 3D Printing in the Clinic

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↗

DOE OSTI2015

MO-B-BRD-03: Principles, Pitfalls and Techniques of 3D Printing for Bolus and Compensators

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↗

DOE OSTI2016

SU-G-IeP2-13: Toward Heavy Ion Computed Tomography with Carbon Ions: A Monte Carlo Study

Purpose: In the present Monte Carlo study, we investigated the use of Carbon ions for computed tomography (CT) with a relatively low imaging dose. This will enable us to avoid any conversion of X-ray CT numbers to the relative stopping power (or relative electron density) values and the associated uncertainties in Carbon dose calculation. Methods: In the first stage, we studied the propagation of Carbon nuclei through a water phantom using the Geant4 specially to understand their lateral displacement inside the phantom. In the second stage, we used our GPU-based Monte Carlo code, which has been cross validated against Geant4, to create the 2D map of the water equivalent path length (WEPL) inside a human head size phantom by acquiring 240 projections each 1.5° apart. Subsequently the 3D relative electron density map of the phantom was reconstructed from the 2D WEPL map using the Algebraic Reconstruction Technique (ART) coupled with total variation (TV) minimization Results: A high quality image of the relative electron density inside the phantom was reconstructed by ARTTV. The mean relative error between the reconstructed image for low contrast object (PMMA) was about 1.74%. The delivered dose per scan at the center of the phantom was about 0.1 Gy. Conclusion: We have been able to obtain a 3D map of the electron density using a human head size phantom while keeping the delivered dose to relatively low value. Using the GPU capabilities of our simulation engine, we believe that a real time CT with Carbon ions could be a reality in future.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2012

A RADIATION TRANSFER SOLVER FOR ATHENA USING SHORT CHARACTERISTICS

We describe the implementation of a module for the Athena magnetohydrodynamics (MHD) code that solves the time-independent, multi-frequency radiative transfer (RT) equation on multidimensional Cartesian simulation domains, including scattering and non-local thermodynamic equilibrium (LTE) effects. The module is based on well known and well tested algorithms developed for modeling stellar atmospheres, including the method of short characteristics to solve the RT equation, accelerated Lambda iteration to handle scattering and non-LTE effects, and parallelization via domain decomposition. The module serves several purposes: it can be used to generate spectra and images, to compute a variable Eddington tensor (VET) for full radiation MHD simulations, and to calculate the heating and cooling source terms in the MHD equations in flows where radiation pressure is small compared with gas pressure. For the latter case, the module is combined with the standard MHD integrators using operator splitting: we describe this approach in detail, including a new constraint on the time step for stability due to radiation diffusion modes. Implementation of the VET method for radiation pressure dominated flows is described in a companion paper. We present results from a suite of test problems for both the RT solver itself and for dynamical problems that include radiative heating and cooling. These tests demonstrate that the radiative transfer solution is accurate and confirm that the operator split method is stable, convergent, and efficient for problems of interest. We demonstrate there is no need to adopt ad hoc assumptions of questionable accuracy to solve RT problems in concert with MHD: the computational cost for our general-purpose module for simple (e.g., LTE gray) problems can be comparable to or less than a single time step of Athena's MHD integrators, and only few times more expensive than that for more general (non-LTE) problems.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

The effects of mapping CT images to Monte Carlo materials on GEANT4 proton simulation accuracy

Purpose: Monte Carlo simulations of radiation therapy require conversion from Hounsfield units (HU) in CT images to an exact tissue composition and density. The number of discrete densities (or density bins) used in this mapping affects the simulation accuracy, execution time, and memory usage in GEANT4 and other Monte Carlo code. The relationship between the number of density bins and CT noise was examined in general for all simulations that use HU conversion to density. Additionally, the effect of this on simulation accuracy was examined for proton radiation. Methods: Relative uncertainty from CT noise was compared with uncertainty from density binning to determine an upper limit on the number of density bins required in the presence of CT noise. Error propagation analysis was also performed on continuously slowing down approximation range calculations to determine the proton range uncertainty caused by density binning. These results were verified with Monte Carlo simulations. Results: In the presence of even modest CT noise (5 HU or 0.5%) 450 density bins were found to only cause a 5% increase in the density uncertainty (i.e., 95% of density uncertainty from CT noise, 5% from binning). Larger numbers of density bins are not required as CT noise will prevent increased density accuracy; this applies across all types of Monte Carlo simulations. Examining uncertainty in proton range, only 127 density bins are required for a proton range error of <0.1 mm in most tissue and <0.5 mm in low density tissue (e.g., lung). Conclusions: By considering CT noise and actual range uncertainty, the number of required density bins can be restricted to a very modest 127 depending on the application. Reducing the number of density bins provides large memory and execution time savings in GEANT4 and other Monte Carlo packages.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-C-BRC-07: Parametrized GPU Accelerated Electron Monte Carlo Second Check

Purpose: I am presenting a parameterized 3D GPU accelerated electron Monte Carlo second check program. Method: I wrote the 3D grid dose calculation algorithm in CUDA and utilized an NVIDIA GeForce GTX 780 Ti to run all of the calculations. The electron path beyond the distal end of the cone is governed by four parameters: the amplitude of scattering (AMP), the mean and width of a Gaussian energy distribution (E and α), and the percentage of photons. In my code, I adjusted all parameters until the calculated PDD and profile fit the measured 10×10 open beam data within 1%/1mm. I then wrote a user interface for reading the DICOM treatment plan and images in Python. In order to verify the algorithm, I calculated 3D dose distributions on a variety of phantoms and geometries, and compared them with the Eclipse eMC calculations. I also calculated several patient specific dose distributions, including a nose and an ear. Finally, I compared my algorithm’s computation times to Eclipse’s. Results: The calculated MU for all of the investigated geometries agree with the TPS within the TG-114 action level of 5%. The MU for the nose was < 0.5 % different while the MU for the ear at 105 SSD was ∼2 %. Calculation times for a 12MeV 10×10 open beam ranged from 1 second for a 2.5 mm grid resolution with ∼15 million particles to 33 seconds on a 1 mm grid with ∼460 million particles. Eclipse calculation runtimes distributed over 10 FAS workers were 9 seconds to 15 minutes respectively. Conclusion: The GPU accelerated second check allows quick MU verification while accounting for patient specific geometry and heterogeneity.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Fast automated analysis of strong gravitational lenses with convolutional neural networks

Quantifying image distortions caused by strong gravitational lensing—the formation of multiple images of distant sources due to the deflection of their light by the gravity of intervening structures—and estimating the corresponding matter distribution of these structures (the ‘gravitational lens’) has primarily been performed using maximum likelihood modelling of observations. Our procedure is typically time- and resource-consuming, requiring sophisticated lensing codes, several data preparation steps, and finding the maximum likelihood model parameters in a computationally expensive process with downhill optimizers. Accurate analysis of a single gravitational lens can take up to a few weeks and requires expert knowledge of the physical processes and methods involved. Tens of thousands of new lenses are expected to be discovered with the upcoming generation of ground and space surveys. We report the use of deep convolutional neural networks to estimate lensing parameters in an extremely fast and automated way, circumventing the difficulties that are faced by maximum likelihood methods. We also show that the removal of lens light can be made fast and automated using independent component analysis of multi-filter imaging data. Our networks can recover the parameters of the ‘singular isothermal ellipsoid’ density profile, which is commonly used to model strong lensing systems, with an accuracy comparable to the uncertainties of sophisticated models but about ten million times faster: 100 systems in approximately one second on a single graphics processing unit. These networks can provide a way for non-experts to obtain estimates of lensing parameters for large samples of data.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

DYNAMICAL FRAGMENTATION OF THE T PYXIDIS NOVA SHELL DURING RECURRENT ERUPTIONS

Hubble Space Telescope images of the ejecta surrounding the nova T Pyxidis resolve the emission into more than 2000 bright knots. We simulate the dynamical evolution of the ejecta from T Pyxidis during its multiple eruptions over the last 150 years using the adaptive mesh refinement code Ramses. We demonstrate that the observed knots are the result of Richtmyer-Meshkov gas dynamical instabilities (the equivalent of Rayleigh-Taylor instabilities in an accelerated medium). These instabilities are caused by the overrunning of the ejecta from the classical nova of 1866 by fast-moving ejecta from the six subsequent recurrent nova outbursts. Magnetic fields may play a role in determining knot scale and preventing their conductive evaporation. The model correctly predicts the observed expansion and dimming of the T Pyx ejecta as well as the knotty morphology. The model also predicts that deeper, high-resolution imagery will show filamentary structure connecting the knots. We show reprocessed Hubble Space Telescope imagery that shows the first hints of such a structure.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2012

HST/ACS PHOTOMETRY OF OLD STARS IN NGC 1569: THE STAR FORMATION HISTORY OF A NEARBY STARBURST

We used Hubble Space Telescope/Advanced Camera for Surveys to obtain deep V- and I-band images of NGC 1569, one of the closest and strongest starburst galaxies in the universe. These data allowed us to study the underlying old stellar population, aimed at understanding NGC 1569's evolution over a full Hubble time. We focus on the less-crowded outer region of the galaxy, for which the color-magnitude diagram (CMD) shows predominantly a red giant branch (RGB) that reaches down to the red clump/horizontal branch feature (RC/HB). A simple stellar population analysis gives clear evidence for a more complicated star formation history (SFH) in the outer region. We derive the full SFH using a newly developed code, SFHMATRIX, which fits the CMD Hess diagram by solving a non-negative least-squares problem. Our analysis shows that the relative brightnesses of the RGB tip and RC/HB, along with the curvature and color of the RGB, provide enough information to ameliorate the age-metallicity-extinction degeneracy. The distance/reddening combination that best fits the data is E(B - V) = 0.58 {+-} 0.03 and D = 3.06 {+-} 0.18 Mpc. Star formation began {approx}13 Gyr ago, and this accounts for the majority of the mass in the outer region. However, the initial burst was followed by a relatively low, but constant, rate of star formation until {approx}0.5-0.7 Gyr ago when there may have been a short, low intensity burst of star formation. Stellar metallicity increases over time, consistent with chemical evolution expectations. The dominant old population shows a considerable spread in metallicity, similar to the Milky Way halo. However, the star formation in NGC 1569's outer region lasted much longer than in the Milky Way. The distance and line-of-sight velocity of NGC 1569 indicate that it has moved through the IC 342 group of galaxies, which may have caused this extended star formation. Comparison with other recent work provides no evidence for radial population gradients in the old population of NGC 1569, suggesting that our results are representative of the old stellar population throughout the galaxy.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Extrusion parameter control optimization for DIW 3D printing using image analysis techniques

Material extrusion is a well-recognized facet of additive manufacturing that involves the fabrication of parts through the deposition of structural material from an extrusion head from a bulk supply. In the subdivision of Direct Ink Writing (DIW) additive manufacturing, challenges arise when the structural material is flowable, synchronous extrusion control and tool movement becomes critical for achieving high-quality parts with low defect populations. DIW techniques are most used in laboratory settings using expensive custom instruments and may require specialized 3D slicing software. Here, in this study, the fabrication of an inexpensive, consumer-friendly progressive cavity pump dispensing system is detailed, in which can create high-quality parts by executing G-code commands produced from a commercial slicing software. The precision and repeatability of the movement-synchronized material extrusion is demonstrated through a series of optimization schemes, entailing the alteration of various control parameters, which directly affect the extrusion properties demonstrated during a print. In situ diagnostics were implemented to evaluate the results of the established optimization experiment. Using a machine vision technique, images of the optimization prints are processed. Following this, a supervised machine learning model was trained to autonomously judge whether or not the extrusion parameters produced a passing or failing result. The machine learning scheme serves as a preliminary benchmark for future layer-by-layer evaluation of more complex DIW parts. The construction of the printer and development of in situ characterization capabilities demonstrates the ability for this printer to create high-fidelity DIW parts for a fraction of the price of other systems.

42 ENGINEERING↗

DOE OSTI2017

Sparse Overcomplete Denoising: Aggregation Versus Global Optimization

Denoising is often addressed via sparse coding with respect to an overcomplete dictionary. There are two main approaches when the dictionary is composed of translates of an orthonormal basis. The first, traditionally employed by techniques such as wavelet cycle spinning, separately seeks sparsity w.r.t. each translate of the orthonormal basis, solving multiple partial optimizations and obtaining a collection of sparse approximations of the noise-free image, which are aggregated together to obtain a final estimate. The second approach, recently employed by convolutional sparse representations, instead seeks sparsity over the entire dictionary via a global optimization. It is tempting to view the former approach as providing a suboptimal solution of the latter. In this letter, we analyze whether global sparsity is a desirable property, and under what conditions the global optimization provides a better solution to the denoising problem. In particular, our experimental analysis shows that the two approaches attain comparable performance in case of natural images and global optimization outperforms the simpler aggregation of partial estimates only when the image admits an extremely sparse representation. Here, we explain this phenomenon by separately studying the bias and variance of these solutions, and by noting that the variance of the global solution increases very rapidly as the original signal becomes less and less sparse.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

SU-F-BRA-06: Dose Distributions for the CivaSheet Pd-103 Directional Brachytherapy Device

Purpose: A flexible polymer membrane (CivaSheet) has been developed by CivaTech Oncology, Inc. (Research Triangle Park, NC) for permanent brachytherapy. Distributed throughout the array are small plastic disks containing Pd-103 and gold foil shielding on one side to provide a directional dose distribution and facilitate imaging. This study evaluated dosimetry for the CivaSheet. Methods: Manufacturer-provided dimensional and compositional information for the device were compared to physical samples for validation of design information, then entered into the MCNP6 radiation transport code for dosimetry simulations. Three device sizes (6×6, 6×12, or 6×18 disk-arrays) were simulated as the membrane can be custom-sized preceding surgical placement. Dose to water was estimated with 0.01 cm resolution from the surface to 10 cm on both sides of the device. Because this is a novel device with calibration methods under development, results were normalized using DVHs to provide 90% prescription coverage to a plane positioned 0.5 cm from the front surfaces. This same normalization was used for creating isodose distributions. Results: Planar dose distributions of flat CivaSheets were relatively homogeneous with acceptable dose uniformity variations. Differences in the results between the differently sized CivaSheets were not significant. At 0.5 mm, 87% of the target volume was within the therapeutic dose range. Dose hotspots on the CivaSheet forward surfaces were directly above the disks. However, dose hotspots on the rear-facing surfaces were positioned between the disks. Doses in contact with the front surface were similar to those observed for currently available brachytherapy sources. Maximum doses that occurred on the rear surface were approximately 55 times lower than the dose on the front surface. Conclusion: Monte Carlo calculations validated the directional capabilities and advantageous dosimetry of the new Pd-103 brachytherapy device. It appears feasible to re-size the CivaSheet in the operating room with an acceptable variation in prescription dose. Research was supported by CivaTech Oncology, Inc.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

MO-B-BRD-01: Creation of 3D Printed Phantoms for Clinical Radiation Therapy

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↗

DOE OSTI2017

Piston geometry effects in a light-duty, swirl-supported diesel engine: Flow structure characterization

This work studied how in-cylinder flow structure is affected in a light-duty, swirl-supported diesel engine when equipped with three different piston geometries: the first two featuring a conventional re-entrant bowl, either with or without valve cut-outs on the piston surface and the third featuring a stepped-lip bowl. Particle image velocimetry experiments were conducted inside an optical engine to measure swirl vortex intensity and structure during the intake and compression strokes. A full computational model of the optical diesel engine was built using the FRESCO code, a recently developed object-oriented parallel computational fluid dynamics platform for engine simulations. The model was first validated against the measured swirl-plane velocity fields, and the simulation convergence for multiple cycles was assessed. Flow topology was studied by addressing bulk flow and turbulence quantities, including swirl structure, squish flux, plus geometric and operating parameters, such as the presence of valve cut-outs on the piston surface, compression ratio and engine speed. The results demonstrated that conventional re-entrant bowls have stronger flow separation at intake, hampering bowl swirl, but higher global swirl than for stepped-lip bowls thanks to a stronger and more axisymmetric squish mechanism and less tilted swirl. Stepped-lip bowls have larger inhomogeneities (tilt and axisymmetry) and higher turbulence levels, but also faster turbulence dissipation toward top dead center. They have weaker squish flux but larger squish inversion momentum as a result of the smaller inertia.

Perini, Federico↗

DOE OSTI2023

Effects of spin-orbit coupling and very large supercells on the description of acceptors in CdTe

Predicting accurate shallow donor and acceptor levels in semiconductors has been quite challenging using periodic boundary conditions as implemented in current density functional theory codes. The reason is that the wave functions associated with the shallow centers are quite extended and are not fully contained in the supercell (typically with a few hundred atoms) so impurities in the periodically repeated image cells interact with each other. Errors of ~0.1 eV are expected, and these are of the same order of magnitude as the ionization energies themselves. In the case of acceptors in CdTe, this problem is exacerbated by the strong spin-orbit coupling that split the Te-related states at the top of the valence band, making the calculations at least 8 times more expensive. CdTe is an important solar-cell material with record high efficiency of 22%. One of the main limiting factors to increasing the efficiency towards the theoretical limit of ~30% is the often reported very low hole concentration. Pushing to the limit of computational capability by using very large supercells with spin-orbit coupling we report the results of hybrid functional calculations of group-V acceptors in CdTe. We show that extrapolation to the dilute limit leads to an interpretation of the experimental data that is qualitatively different from previous DFT and hybrid functional calculation reports. We find that the group-V impurities indeed behave as shallow acceptors and that the corresponding compensating AX-centers are unstable and do not limit p-type doping. We address the differences between our results and previous theoretical predictions and show that our calculated ionization energies predict hole concentrations that are in excellent agreement with recent temperature-dependent Hall measurements on high-quality single-crystal samples.

14 SOLAR ENERGY↗

DOE OSTI2023

Few-Shot Learning Enables Population-Scale Analysis of Leaf Traits in Populus trichocarpa

Plant phenotyping is typically a time-consuming and expensive endeavor, requiring large groups of researchers to meticulously measure biologically relevant plant traits, and is the main bottleneck in understanding plant adaptation and the genetic architecture underlying complex traits at population scale. In this work, we address these challenges by leveraging few-shot learning with convolutional neural networks to segment the leaf body and visible venation of 2,906 Populus trichocarpa leaf images obtained in the field. In contrast to previous methods, our approach (a) does not require experimental or image preprocessing, (b) uses the raw RGB images at full resolution, and (c) requires very few samples for training (e.g., just 8 images for vein segmentation). Traits relating to leaf morphology and vein topology are extracted from the resulting segmentations using traditional open-source image-processing tools, validated using real-world physical measurements, and used to conduct a genome-wide association study to identify genes controlling the traits. In this way, the current work is designed to provide the plant phenotyping community with (a) methods for fast and accurate image-based feature extraction that require minimal training data and (b) a new population-scale dataset, including 68 different leaf phenotypes, for domain scientists and machine learning researchers. All of the few-shot learning code, data, and results are made publicly available.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

How do magnetized HED flows transition to collimated plasma jets? (Final Report)

We present results from a pulsed-power experiment designed to generate accretion-like flows in the laboratory that may be used to study the dynamics of astrophysical accretion-driven outflows. To emulate systems like Young Stellar Object (YSO) outflows, we create radially converging plasma flows in a short disk that transition into much longer bipolar outflows. Our experiment uses a ~1 MA pulsed-power driver to generate plasma from an array of thin aluminum wires mounted to a 3D-printed current path that controls the angular momentum and magnetic field topology. In this paper, we show that experimental data scale favorably to observed properties of YSO jets. This set of experiments tests the simplest version of our possible plasma dynamics, where outflows are generated without rotation or axial magnetic field present. The temperature, velocity and density of the disk and outflows are characterized using interferometry, gated optical and ultraviolet imaging, and Thomson scattering diagnostics. We discuss the Reynolds number, magnetic Reynolds number and Mach numbers calculated in three different stages of the experiment, and compare our results to 3D numerical simulations in the PERSEUS magnetohydrodynamics code. This report is a summary of the work done by the graduate students who were supported by the project.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2015

An array of virtual Frisch-grid CdZnTe detectors and a front-end application-specific integrated circuit for large-area position-sensitive gamma-ray cameras

We developed a robust and low-cost array of virtual Frisch-grid CdZnTe (CZT) detectors coupled to a front-end readout ASIC for spectroscopy and imaging of gamma rays. The array operates as a self-reliant detector module. It is comprised of 36 close-packed 6x6x15 mm 3 detectors grouped into 3x3 sub-arrays of 2x2 detectors with the common cathodes. The front-end analog ASIC accommodates up to 36 anode and 9 cathode inputs. Several detector modules can be integrated into a single- or multi-layer unit operating as a Compton or a coded-aperture camera. We present the results from testing two fully assembled modules and readout electronics. The further enhancement of the arrays’ performance and reduction of their cost are made possible by using position-sensitive virtual Frisch-grid detectors, which allow for accurate corrections of the response of material non-uniformities caused by crystal defects.

36 MATERIALS SCIENCE↗