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At least 433 records · Page 24

Holographic interferometry applied to symmetric aerodynamic models in a wind tunnel

The technique of holographic interferometry provides a means for noninvasive measurement of the air density distribution in the flow field in the vicinity of an aerodynamic model. A test of the applicability of this technique was the objective of this investigation. A holographic interferometer was installed in the 2- by 2-Foot Transonic Wind Tunnel at Ames Research Center. Several tests were conducted with this system on two axisymmetric models, one at subsonic and the other at supersonic speeds. Holograms were made of the flow field around the model for several test conditions. These holograms were reconstructed into interferograms in the laboratory. The fringe distribution (a measure of local densities) from a number of interferograms was digitized for subsequent data reduction. A computer program based on the Fourier transform technique was developed to convert the fringe distribution into a three-dimensional distribution of air density around the model. These results will be presented in this paper.

Perry, R. L.↗

Black-box optimization of CT acquisition and reconstruction parameters: a reinforcement learning approach

Protocol optimization is critical in Computed Tomography (CT) for achieving desired diagnostic image quality while minimizing radiation dose. Due to the inter-effect of influencing CT parameters, traditional optimization methods rely on the testing of exhaustive combinations of these parameters. This poses a notable limitation due to the impracticality of exhaustive parameter testing. This study introduces a novel methodology leveraging Virtual Imaging Trials (VITs) and reinforcement learning to more efficiently optimize CT protocols. Computational phantoms with liver lesions were imaged using a validated CT simulator and reconstructed with a novel CT reconstruction Toolkit. The optimization parameter space included tube voltage, tube current, reconstruction kernel, slice thickness, and pixel size. The optimization process was done using a Proximal Policy Optimization (PPO) agent which was trained to maximize the Detectability Index (d’) of the liver lesion for each reconstructed image. Results showed that our reinforcement learning approach found the absolute maximum d’ across the test cases while requiring 79.7% fewer steps compared to an exhaustive search, demonstrating both accuracy and computational efficiency, offering a efficient and robust framework for CT protocol optimization. The flexibility of the proposed technique allows for use of varying image quality metrics as the objective metric to maximize for. Our findings highlight the advantages of combining VIT and reinforcement learning for CT protocol management.

Fenwick, David [Duke University Medical Center]↗

Optical read/write memory system components

The optical components of a breadboard holographic read/write memory system have been fabricated and the parameters specified of the major system components: (1) a laser system; (2) an x-y beam deflector; (3) a block data composer; (4) the read/write memory material; (5) an output detector array; and (6) the electronics to drive, synchronize, and control all system components. The objectives of the investigation were divided into three concurrent phases: (1) to supply and fabricate the major components according to the previously established specifications; (2) to prepare computer programs to simulate the entire holographic memory system so that a designer can balance the requirements on the various components; and (3) to conduct a development program to optimize the combined recording and reconstruction process of the high density holographic memory system.

Kozma, A.↗

Selection Algorithm for electron neutrino charged current interactions in SBND

The Short Baseline Neutrino (SBN) program at Fermilab is a joint proposal by three experimental collaborations primarily for the investigation of the cause behind the low-energy electron-like event excess observed by the MiniBoone experiment. This dissertation focuses on the near detector of the project, named the Short Baseline Near Detector (SBND), a Liquid Argon Time Projection Chamber apparatus which will conduct searches for sterile neutrinos in the mass range of 1 ${eV}^2/{c}^4$, as well as provide cross-section measurements for neutrino interactions in argon and perform other beyond the standard model studies.\\ \indent As is the case for all detectors in the program, the SBND will use the Booster Neutrino Beam as its source, which will provide it with both muon and electron neutrinos. Given that the ability to discern between the neutrino flavors will be crucial to the fulfillment of the detector's physics goals, the objective of this work is to provide the collaboration with a tool capable of doing so. As such, we here present the development process for an inclusive selection algorithm for the identification of electron neutrino charged current (CC) events regardless of their interaction channel. This is done through a combination of traditional techniques, such as the implementation of cuts on the reconstructed interaction properties, with the use of the Convolutional Visual Network, a machine learning algorithm capable of classifying particle interactions through the analysis of the topology of their final states. With this approach, we have developed a selection process that is capable of identifying $\nu_e$ CC interactions across a wide range of topologies with 34.4\% efficiency, as well as a purity of 91.2\%, making it especially promising for use in cross section studies.

Freire, Hector Moya [ABC Federal U.] (ORCID:000900↗

Optimisation of large-radius jet reconstruction for the ATLAS detector in 13 TeV proton–proton collisions

Jet substructure has provided new opportunities for searches and measurements at the LHC, and has seen continuous development since the optimization of the large-radius jet definition used by ATLAS was performed during Run 1. A range of new inputs to jet reconstruction, pile-up mitigation techniques and jet grooming algorithms motivate an optimisation of large-radius jet reconstruction for ATLAS. In this paper, this optimisation procedure is presented, and the performance of a wide range of large-radius jet definitions is compared. The relative performance of these jet definitions is assessed using metrics such as their pileup stability, ability to identify hadronically decaying W bosons and top quarks with large transverse momenta. A new type of jet input object, called a ‘unified flow object’ is introduced which combines calorimeter- and inner-detector-based signals in order to achieve optimal performance across a wide kinematic range. Large-radius jet definitions are identified which significantly improve on the current ATLAS baseline definition, and their modelling is studied using pp collisions recorded by the ATLAS detector at √s = 13 TeV

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Solution algorithms for the two-dimensional Euler equations on unstructured meshes

The objective of the study was to analyze implicit techniques employed in structured grid algorithms for solving two-dimensional Euler equations and extend them to unstructured solvers in order to accelerate convergence rates. A comparison is made between nine different algorithms for both first-order and second-order accurate solutions. Higher-order accuracy is achieved by using multidimensional monotone linear reconstruction procedures. The discussion is illustrated by results for flow over a transonic circular arc.

Whitaker, D. L.↗

Pointing History Engine for the Spitzer Space Telescope

The Pointing History Engine (PHE) is a computer program that provides mathematical transformations needed to reconstruct, from downlinked telemetry data, the attitude of the Spitzer Space Telescope (formerly known as the Space Infrared Telescope Facility) as a function of time. The PHE also serves as an example for development of similar pointing reconstruction software for future space telescopes. The transformations implemented in the PHE take account of the unique geometry of the Spitzer telescope-pointing chain, including all data on relative alignments of components, and all information available from attitude-determination instruments. The PHE makes it possible to coordinate attitude data with observational data acquired at the same time, so that any observed astronomical object can be located for future reference and re-observation. The PHE is implemented as a subroutine used in conjunction with telemetry-formatting services of the Mission Image Processing Laboratory of NASA s Jet Propulsion Laboratory to generate the Boresight Pointing History File (BPHF). The BPHF is an archival database designed to serve as Spitzer s primary astronomical reference documenting where the telescope was pointed at any time during its mission.

Bayard, David↗

Research on infrared astrophysics and X ray and XUV astronomy

The infrared research was divided into two related subjects, observations at wavelengths less than 34 microns and millimeter wavelength observations. A new complex of infrared sources in the Orion Nebula observed along with a broad range of galactic and extragalactic objects. The Comet Kohoutek was measured in the 1-20 micron wavelength region and its thermal properties agreed closely with those of Comet Ikeya-Seki. Combined infrared and photoelectric studies of the Makarian galaxies showed them to have a composite spectrum with a large emission feature in the far infrared. The development of one millimeter photometry and composited bolometers is described. A technique of reconstructing two dimensional surface brightness distributions with appropriate errors from individual strip scans was developed. Model parameters were determined by fitting data in non-linear systems. Results show spectral parameter uncertainties are underestimated or incorrectly evaluated in most studies.

Source record↗

COSMIC: A high resolution, large collecting area telescope

The spaceborne Coherent Optical System of Modular Imaging Collectors (COSMIC) is presented. It has high angular resolution and can produce images of complex, low-surface-brightness objects such as distant galaxies. If configured as a 36 m filled linear array, COSMIC can have 15 times better angular resolution and 10 times greater collecting area than the Space Telescope. Alternatively, if the collecting area is spread out to create an unfilled two-dimensional array, there is the additional advantage of not needing to rotate the array in order to build up a reconstructed image. Considerations which led to the design concept, scientific goals, and the potentially useful role of a space station for assembly are discussed.

Traub, W. A.↗

Recent Developments to the Porous Microstructure Analysis (PuMA) Software

Introduction The Porous Microstructure Analysis (PuMA) software is an open source framework for image-based simulation, primarily used to determine effective properties based on material microstructure. PuMA was originally developed for the study of NASA thermal protection materials; however, many of the solvers in PuMA have applicability to a broad range of materials science applications. PuMA version 3.2 computes material surface area, pore diameters, effective thermal conductivity, continuum and rarefied tortuosity, and permeability. For anisotropic materials, PuMA can estimate material orientation and compute anisotropic thermal conductivity and elasticity. In this talk, a brief overview of the PuMA software and underlying methods will be presented, as well as some recent and ongoing developments, including the use of immersed boundary methods for image-based simulation and the development of a new weave segmentation tool, called TomoSAM. Cut-Cell method for heat and mass transfer For simulations on complex microstructures, traditional unstructured meshing techniques often prove to be difficult and time-intensive. Voxel-based solvers, which represent the surface as a staircase structure, are relatively simple to implement but can lose accuracy when feature resolution is poor. In this work, we present a novel 3D cut-cell method for solving the variable coefficient Poisson equation on complex microstructures, suitable for the determination of effective thermal conductivity or tortuosity of a material. The method uses a Marching Cubes/Marching Squares surface reconstruction to create cut-cells and determine geometric quantities. A flux-correction method is extended to 3D, with least squares gradient reconstruction, to solve for the boundary fluxes in the cut-cells. Verification cases show the solver achieves globally 2nd order accuracy on complex microstructures. TomoSAM TomoSAM, a module of the PuMA software, has been developed as a plugin for 3D Slicer, a software platform used for 3D image processing and visualization. It utilizes the Segment Anything Model (SAM), a deep learning model capable of identifying objects and generating image masks based on minimal user input. This feature enables efficient segmentation of complex 3D datasets, particularly of woven materials, from tomography or similar imaging methods, reducing the need for manual segmentation.

Tomography↗

Recent Developments to the Porous Microstructure Analysis (PuMA) Software

The Porous Microstructure Analysis (PuMA) software is an open source framework for image-based simulation, primarily used to determine effective properties based on material microstructure. PuMA was originally developed for the study of NASA thermal protection materials; however, many of the solvers in PuMA have applicability to a broad range of materials science applications. PuMA version 3.2 computes material surface area, pore diameters, effective thermal conductivity, continuum and rarefied tortuosity, and permeability. For anisotropic materials, PuMA can estimate material orientation and compute anisotropic thermal conductivity and elasticity. In this talk, a brief overview of the PuMA software and underlying methods will be presented, as well as some recent and ongoing developments, including the use of immersed boundary methods for image-based simulation and the development of a new weave segmentation tool, called TomoSAM. Cut-Cell method for heat and mass transfer For simulations on complex microstructures, traditional unstructured meshing techniques often prove to be difficult and time-intensive. Voxel-based solvers, which represent the surface as a staircase structure, are relatively simple to implement but can lose accuracy when feature resolution is poor. In this work, we present a novel 3D cut-cell method for solving the variable coefficient Poisson equation on complex microstructures, suitable for the determination of effective thermal conductivity or tortuosity of a material. The method uses a Marching Cubes/Marching Squares surface reconstruction to create cut-cells and determine geometric quantities. A flux-correction method is extended to 3D, with least squares gradient reconstruction, to solve for the boundary fluxes in the cut-cells. Verification cases show the solver achieves globally 2nd order accuracy on complex microstructures. TomoSAM TomoSAM, a module of the PuMA software, has been developed as a plugin for 3D Slicer, a software platform used for 3D image processing and visualization. It utilizes the Segment Anything Model (SAM), a deep learning model capable of identifying objects and generating image masks based on minimal user input. This feature enables efficient segmentation of complex 3D datasets, particularly of woven materials, from tomography or similar imaging methods, reducing the need for manual segmentation.

Tomography↗

Time-resolved diffusion tomographic imaging in highly scattering turbid media

A method for imaging objects in highly scattering turbid media. According to one embodiment of the invention, the method involves using a plurality of intersecting source/detectors sets and time-resolving equipment to generate a plurality of time-resolved intensity curves for the diffusive component of light emergent from the medium. For each of the curves, the intensities at a plurality of times are then inputted into the following inverse reconstruction algorithm to form an image of the medium: X.sup.(k+1).spsp.T =?Y.sup.T W+X.sup.(k).spsp.T .LAMBDA.!?W.sup.T W+.LAMBDA.!.sup.-1 wherein W is a matrix relating output at detector position r.sub.d, at time t, to source at position r.sub.s, .LAMBDA. is a regularization matrix, chosen for convenience to be diagonal, but selected in a way related to the ratio of the noise, to fluctuations in the absorption (or diffusion) X.sub.j that we are trying to determine: .LAMBDA..sub.ij =.lambda..sub.j .delta..sub.ij with .lambda..sub.j = /<.DELTA.Xj.DELTA.Xj> Here Y is the data collected at the detectors, and X.sup.k is the kth iterate toward the desired absoption information.

Alfano, Robert R.↗

Exploring the Great Pyramid

For centuries, the pyramids at Giza have been the object of frequent speculation and study. L. Alvarez et al. in 1970 and the ScanPyramids collaboration in 2017 have very successfully implemented HEP detector technology to image the pyramid of Khafre and the Great Pyramid of Khufu, respectively. Numerous questions about Khufu’s structure remain, however. The EGP project aims to undertake a new study of this enigmatic monument’s interior by applying high-resolution tomographic imaging and reconstruction, which will permit a detailed understanding of internal variations in density and may offer insight regarding exactly how Egypt’s largest pyramid was built.

43 PARTICLE ACCELERATORS↗

Tomographic decoding algorithm for a nonoverlapping redundant array

A tomographic reconstruction algorithm is developed for the nonoverlapping redundant array X-ray imaging system whereby the background contributions from out-of-focus planes can be eliminated. The algorithm makes use of two constraints derived from the physical characteristics of the nonoverlapping redundant array system in tandem with the correlation decoding process. It is simple, direct, and noniterative. Tomographic images of computer-generated planar and three-dimensional objects are provided to illustrate the effectiveness of the algorithm.

Yin, Lo I.↗

Large-scale structure effects on the gravitational lens image positions and time delay

We compute the fluctuations in gravitational lens image positions and time delay caused by large-scale structure correlations. We show that these fluctuations can be expressed as a simple integral over the density power spectrum. Using the Cosmic Background Explorer (COBE) normalization we find that positions of objects at cosmological distances are expected to deviate from their true positions by few arcminutes. These deflections are not directly observable. The positions of the images relative to one another fluctuate by a few percent of the relative separation, implying that one does not expect multiple images to be produced by large-scale structure. Nevertheless, the fluctuations are larger than the observational errors on the positions and affect reconstructions of the lens potential. The time delay fluctuations have a geometrical and a gravitational contribution. Both are much larger than the expected time delay from the primary lens, but partially cancel each other. We find that large-scale structure weakly affects the time delay and time delay measurements can be used as a probe of the distance scale in the universe.

Seljak, Uros↗

Coded-mask-based X-ray phase-contrast and dark-field imaging

Phase contrast and dark-field X-ray imaging enable imaging of objects that absorb or reflect very little X-ray light. Disclosed is a method and systems for performing coded-mask-based multi-contrast imaging (CMMI). The method includes providing radiation to a coded mask that has a known phase and absorption profile according to a pre-determined pattern. The radiation is then impingent upon a sample, and the radiation is detected to perform phase-reconstruction and image processing. The method and associated systems allow for the use of maximum-likelihood and machine learning methods for reconstruction images of the sample from the detected radiation.

Shi, Xianbo↗

Segmentation of RDX and TNT in X‐Ray Computed Tomography Reconstructions of Melt‐Cast Explosives

ABSTRACT Three‐dimensional mesoscale characterization of heterogeneous melt‐cast high explosives is challenging because of the difficulty differentiating binder from explosive crystals: two functionally different materials which are typically similar in density by design. Here, we report an algorithm which can differentiate hexahydro‐1,3,5‐trinitro‐1,3,5‐triazine (RDX) from 2,4,6‐trinitrotoluene (TNT) in x‐ray computed tomography (CT) volumes with tens of microns resolution. This method allows us to quantify RDX/TNT content, porosity, and RDX domain size. We calibrated the segmentation algorithm using simulated x‐ray CT volumes containing object models of RDX crystals within a TNT matrix. We then segmented and analyzed CT data for Composition B (Comp B), a 60/40 RDX/TNT mixture, and Cyclotol, a 75/25 RDX/TNT mixture. We examined melt‐cast samples fabricated with 100% theoretical maximum density (TMD) and 85% TMD. For the 100% TMD Comp B and Cyclotol samples, the RDX content values calculated by segmentation were 3% and 9% lower, respectively, than the values measured by high‐performance liquid chromatography on material from the same synthesis lots. This result is consistent with the expected underreporting of RDX content resulting from x‐ray CT resolution limits on RDX particles with diameters smaller than 25 µm. The 85% TMD samples were less accurately segmented with our algorithm due to the confounding presence of voids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development and Testing of a High-Precision Position and Attitude Measuring System for a Space Mechanism

This paper describes a high-precision optical metrology system - a unique ground test equipment which was designed and implemented for simultaneous precise contactless measurements of 6 degrees-of-freedom (3 translational + 3 rotational) of a space mechanism end-effector [1] in a thermally controlled ISO 5 clean environment. The developed contactless method reconstructs both position and attitude of the specimen from three cross-sections measured by 2D distance sensors [2]. The cleanliness is preserved by the hermetic test chamber filled with high purity nitrogen. The specimen's temperature is controlled by the thermostat [7]. The developed method excludes errors caused by the thermal deformations and manufacturing inaccuracies of the test jig. Tests and simulations show that the measurement accuracy of an object absolute position is of 20 micron in in-plane measurement (XY) and about 50 micron out of plane (Z). The typical absolute attitude is determined with an accuracy better than 3 arcmin in rotation around X and Y and better than 10 arcmin in Z. The metrology system is able to determine relative position and movement with an accuracy one order of magnitude lower than the absolute accuracy. Typical relative displacement measurement accuracies are better than 1 micron in X and Y and about 2 micron in Z. Finally, the relative rotation can be measured with accuracy better than 20 arcsec in any direction.

Khanenya, Nikolay↗