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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A knock-on deuteron imager for measurements of fuel and hotspot asymmetry in direct-drive inertial confinement fusion implosions (invited)

A knock-on deuteron imager (KoDI) has been implemented to measure the fuel and hotspot asymmetry of cryogenic inertial confinement fusion implosions on OMEGA. Energetic neutrons produced by D–T fusion elastically scatter (“knock on”) deuterons from the fuel layer with a probability that depends on ρR. Deuterons above 10 MeV are produced by near-forward scattering, and imaging them is equivalent to time-integrated neutron imaging of the hotspot. Deuterons below 6 MeV are produced by a combination of side scattering and ranging in the fuel, and encode information about the spatial distribution of the dense fuel. Here, the KoDI instrument consists of a multi-penumbral aperture positioned 10–20 cm from the implosion using a ten-inch manipulator and a detector pack at 350 cm from the implosion to record penumbral images with magnification of up to 35×. Range filters and the intrinsic properties of CR-39 are used to distinguish different charged-particle images by energy along the same line of sight. Image plates fielded behind the CR-39 record a 10 keV x-ray image using the same aperture. A maximum-likelihood reconstruction algorithm has been implemented to infer the source from the projected penumbral images. The effects of scattering and aperture charging on the instrument point-spread function are assessed. Synthetic data are used to validate the reconstruction algorithm and assess an appropriate termination criterion. Significant aperture charging has been observed in the initial experimental dataset, and increases with aperture distance from the implosion, consistent with a simple model of charging by laser-driven EMP.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Image Reconstruction from Sparse-view Data Acquired with Portable X-ray Devices

• Portable X-ray systems enable on-site 3D imaging for non-invasive inspection of suspicious packages and explosives. • Existing reconstruction algorithms (e.g., FDK or Feldkamp, Davis and Kress) require hundreds of projections over 360 degrees. • Sparse-view scan reduces scanning time and setup effort, making it ideal for field use in timecritical scenarios. • Existing reconstruction algorithms introduce severe artifacts when applied to sparse-view data. • We developed a total variation (TV)-based optimization algorithm for yielding 3D images from sparse-view data collected with our portable X-ray imaging system.

Xia, Dan [University of Chicago, Chicago, IL]↗
DOE OSTI2022

Neural net modeling of equilibria in NSTX-U

Neural networks (NNs) offer a path towards synthesizing and interpreting data on faster timescales than traditional physics-informed computational models. In this work we develop two NNs relevant to equilibrium and shape control modeling, which are part of a suite of tools being developed for the National Spherical Torus Experiment-Upgrade for fast prediction, optimization, and visualization of plasma scenarios. The networks include Eqnet, a free-boundary equilibrium solver trained on the EFIT01 (Equilibrium FITtting 01) reconstruction algorithm, and Pertnet, which is trained on the Gspert code and predicts the non-rigid plasma response, a nonlinear term that arises in shape control modeling. The NNs are trained with different combinations of inputs and outputs in order to offer flexibility in use cases. In particular, Eqnet can use magnetic diagnostics as inputs and act as an EFIT-like reconstruction algorithm, or, by using pressure and current profile information the NN can act as a forward Grad–Shafranov equilibrium solver. This forward-mode version is envisioned to be implemented in the suite of tools for simulation of plasma scenarios. The reconstruction-mode version gives some performance improvements compared to the online reconstruction code real-time EFIT, especially when vessel eddy currents are significant. Here, we report strong performance for all NNs indicating that the models could reliably be used within closed-loop simulations or other applications. Some limitations are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Using Cosmic Ray Muons to Assess Geological Characteristics in the Subsurface

Cosmic rays are energetic nuclei and elementary particles that originate from stars and intergalactic events. The interaction of these particles with the upper atmosphere produces a wide range of secondary particles that reach the surface of the earth, of which muons are the most prominent. With enough energy, muons can travel up to a few kilometers beneath the surface of the earth before being stopped completely. The terrestrial muon flux profile and associated zenith angle can be utilized to determine geological characteristics of a location (e.g., rock overburden and density) without having to use conventional methods such as boreholes. This work uses a low-power plastic scintillator-based muon detection system as a prototype for this non-destructive geological assay methodology. Four custom designed 102 cm x 51 cm x 5 cm plastic scintillation panels are used to realize two orthogonal detection planes. Optical photons from each scintillation panel are read using OnSemi J-Series 4x4 silicon photomultiplier (SiPM) arrays in conjunction with preamplifiers. Simultaneous triggers between detectors from two planes indicate a coincidence event which is recorded using the QuarkNet data acquisition system (DAQ) from Fermi National Accelerator Laboratory. A custom detector holder was designed to securely mount the detection system and rotate the panels along the zenith to collect data at variable angles. In order to quantify the systematic uncertainties associated with the detector, such as energy depositions and angular resolution of the detector design, a Monte Carlo (MC) simulation using Geant4 is being developed. Cosmic ray flux prediction will be included in the project by adding the CORSIKA MC code to the simulation toolchain. Simulated and experimental data will drive the development and validation of a reconstruction algorithm that, upon completion, is expected to predict average overburden and rock density. Extended detector exposure to muons can be used as a means to understand changes in the surrounding environment like rock porosity. On the experimental front, muons will initially be measured at the surface, establishing the baseline flux. This is followed by recording the muon flux at variable depths and zenith angles, where the data will be used by the reconstruction algorithm to predict the overburden. The result will be benchmarked against geological surveys. The measured flux data will also be used to benchmark independent and established models. Successful proof-of-concept demonstration of this technology can open doors for long term non-invasive geological monitoring. The detector design, experimental methodology, and the benchmarking efforts are detailed in this work.

Gadey, Harish Reddy↗
DOE OSTI2023

Robust reconstruction of single-cell RNA-seq data with iterative gene weight updates

Single-cell RNA-sequencing technologies have greatly enhanced our understanding of heterogeneous cell populations and underlying regulatory processes. However, structural (spatial or temporal) relations between cells are lost during cell dissociation. These relations are crucial for identifying associated biological processes. Many existing tissue-reconstruction algorithms use prior information about subsets of genes that are informative with respect to the structure or process to be reconstructed. When such information is not available, and in the general case when the input genes code for multiple processes, including being susceptible to noise, biological reconstruction is often computationally challenging. We propose an algorithm that iteratively identifies manifold-informative genes using existing reconstruction algorithms for single-cell RNA-seq data as subroutine. We show that our algorithm improves the quality of tissue reconstruction for diverse synthetic and real scRNA-seq data, including data from the mammalian intestinal epithelium and liver lobules.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Model-Based Reconstruction for Multi-Frequency Collimated Beam Ultrasound Systems

Collimated beam ultrasound systems are a technology for imaging inside multi-layered structures such as geothermal wells. These systems work by using a collimated narrow-band ultrasound transmitter that can penetrate through multiple layers of heterogeneous material. A series of measurements can then be made at multiple transmit frequencies. However, commonly used reconstruction algorithms such as Synthetic Aperture Focusing Technique (SAFT) tend to produce poor quality reconstructions for these systems both because they do not model collimated beam systems and they do not jointly reconstruct the multiple frequencies. Here, in this article, we propose a multi-frequency ultrasound model-based iterative reconstruction (UMBIR) algorithm designed for multi-frequency collimated beam ultrasound systems. The combined system targets reflective imaging of heterogeneous, multi-layered structures. For each transmitted frequency band, we introduce a physics-based forward model to accurately account for the propagation of the collimated narrow-band ultrasonic beam through the multi-layered media. We then show how the joint multi-frequency UMBIR reconstruction can be computed by modeling the direct arrival signals, detector noise, and incorporating a spatially varying image prior. Results using both simulated and experimental data indicate that multi-frequency UMBIR reconstruction yields much higher reconstruction quality than either single frequency UMBIR or SAFT.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Experimental demonstration of coupled multi-peak Bragg coherent diffraction imaging with genetic algorithms

Bragg coherent diffraction imaging has the potential to provide significant insight into the structure-properties relationship for crystalline materials by imaging, with nanoscale resolution, three-dimensional strain fields within individual grains and nanoparticles. The capability of present-day synchrotrons to locate and measure a multiplicity of Bragg reflections from a single grain makes it possible to recover the full strain tensor with nanometer resolution. Recent methods for coupling reconstructions from several peaks to determine the strain tensor have been developed and applied to synthetic data, but have not been applied to experimental data. Here, using a coupled genetic reconstruction algorithm, we reconstruct an experimental data set and demonstrate improvements in the ability to resolve vector-valued displacement fields internal to the particle as compared to what is achieved with a noncoupled approach. The coupled approach developed in this work was also validated on simulated data sets. In both simulated and experimental data, reconstructions from our coupled Bragg peak algorithm show improvements over the noncoupled independent reconstruction method of 5% in terms of accuracy and 53% in terms of consistency.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Tomographic Sparse View Selection Using the View Covariance Loss

Standard computed tomography (CT) reconstruction algorithms such as filtered back projection (FBP) and Feldkamp-Davis-Kress (FDK) require many views for producing high-quality reconstructions, which can slow image acquisition and increase cost in non-destructive evaluation (NDE) applications. Over the past 20 years, a variety of methods have been developed for computing high-quality CT reconstructions from sparse views. However, the problem of how to select the best views for CT reconstruction remains open. In this paper, we present a novel view covariance loss (VCL) function that measures the joint information of a set of views by approximating the normalized mean squared error (NMSE) of the reconstruction. We present fast algorithms for computing the VCL along with an algorithm for selecting a subset of views that approximately minimizes its value. Our experiments on simulated and measured data indicate that for a fixed number of views our proposed view covariance loss selection (VCLS) algorithm results in reconstructions with lower NRMSE, fewer artifacts, and greater accuracy than current alternative approaches.

Lin, Jingsong [Purdue University]↗
DOE OSTI2022

A Common Tracking Software Project

Abstract The reconstruction of the trajectories of charged particles, or track reconstruction, is a key computational challenge for particle and nuclear physics experiments. While the tuning of track reconstruction algorithms can depend strongly on details of the detector geometry, the algorithms currently in use by experiments share many common features. At the same time, the intense environment of the High-Luminosity LHC accelerator and other future experiments is expected to put even greater computational stress on track reconstruction software, motivating the development of more performant algorithms. We present here A Common Tracking Software (ACTS) toolkit, which draws on the experience with track reconstruction algorithms in the ATLAS experiment and presents them in an experiment-independent and framework-independent toolkit. It provides a set of high-level track reconstruction tools which are agnostic to the details of the detection technologies and magnetic field configuration and tested for strict thread-safety to support multi-threaded event processing. We discuss the conceptual design and technical implementation of ACTS, selected applications and performance of ACTS, and the lessons learned.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

End–to–End Metasurface Design for Temperature Imaging via Broadband Planck‐Radiation Regression

A theoretical framework is presented for temperature imaging from long-wavelength infrared (LWIR) thermal radiation (e.g., 8–12 µm) through the end-to-end design of a metasurface-optics frontend and a computational-reconstruction backend. A new nonlinear reconstruction algorithm, “Planck regression”, is introduced to reconstruct the temperature map from a gray scale sensor image, even in the presence of severe chromatic aberration, by exploiting black body and optical physics particular to thermal imaging. This algorithm is combined with an end-to-end approach that optimizes manufacturable, single-layer metasurfaces to yield the most accurate reconstruction. The designs demonstrate high-quality, noise-robust reconstructions of arbitrary temperature maps (including completely random images) in simulations of an ultra-compact thermal-imaging device. Here, it is also shown that Planck regression is much more generalizable to arbitrary images than a straightforward neural-network reconstruction, which requires a large training set of domain-specific images.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Model-based iterative reconstruction with adaptive regularization for artifact reduction in electron tomography

Obtaining high-quality 3D reconstructions from electron tomography of crystalline particles embedded in lighter support elements is crucial for various material systems such as catalysts for fuel cell applications. However, significant challenges arise due to the limited tilt range, sparse and low signal-to-noise ratio of the measurements. In addition, small metal particles can cause strong streaking and shading artifacts in the 3D reconstructions when using conventional reconstruction algorithms due to the presence of Bragg diffraction and the large scattering cross-section difference between the materials of the particles and the background support regions. These artifacts lead to errors in the downstream characterization affecting extraction of critical features such as the size of the metal particles, their distribution and the volume of the lighter support regions. In this paper, we present a two-stage algorithm based on metal artifact reduction, utilizing model-based iterative reconstruction methods with adaptive adjustment of regularization parameters. Our approach yields high-quality 3D reconstructions compared to traditional algorithms, accurately capturing both the metal particles as well as the background support. We demonstrate the effectiveness of our algorithm through simulated and experimental bright-field electron tomography data, showing significant improvements in reconstruction quality compared to traditional methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

TDCOSMO. IX. Systematic comparison between lens modelling software programs: time delay prediction for WGD 2038-4008

The importance of alternative methods for measuring the Hubble constant, such as time-delay cosmography, is highlighted by the recent Hubble tension. It is paramount to thoroughly investigate and rule out systematic biases in all measurement methods before we can accept new physics as the source of this tension. In this study, we perform a check for systematic biases in the lens modelling procedure of time-delay cosmography by comparing independent and blind time-delay predictions of the system WGD 2038-4008 from two teams using two different software programs: GLEE and LENSTRONOMY. The predicted time delays from the two teams incorporate the stellar kinematics of the deflector and the external convergence from line-of-sight structures. The un-blinded time-delay predictions from the two teams agree within 1.2σ, implying that once the time delay is measured the inferred Hubble constant will also be mutually consistent. However, there is a ~4σ discrepancy between the power-law model slope and external shear, which is a significant discrepancy at the level of lens models before the stellar kinematics and the external convergence are incorporated. We identify the difference in the reconstructed point spread function (PSF) to be the source of this discrepancy. When the same reconstructed PSF was used by both teams, we achieved excellent agreement, within ~0.6σ<, indicating that potential systematics stemming from source reconstruction algorithms and investigator choices are well under control. We recommend that future studies supersample the PSF as needed and marginalize over multiple algorithms or realizations for the PSF reconstruction to mitigate the systematics associated with the PSF. A future study will measure the time delays of the system WGD 2038-4008 and infer the Hubble constant based on our mass models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

tomoCAM : fast model-based iterative reconstruction via GPU acceleration and non-uniform fast Fourier transforms

X-ray-based computed tomography is a well established technique for determining the three-dimensional structure of an object from its two-dimensional projections. In the past few decades, there have been significant advancements in the brightness and detector technology of tomography instruments at synchrotron sources. These advancements have led to the emergence of new observations and discoveries, with improved capabilities such as faster frame rates, larger fields of view, higher resolution and higher dimensionality. These advancements have enabled the material science community to expand the scope of tomographic measurements towards increasingly in situ and in operando measurements. In these new experiments, samples can be rapidly evolving, have complex geometries and restrictions on the field of view, limiting the number of projections that can be collected. In such cases, standard filtered back-projection often results in poor quality reconstructions. Iterative reconstruction algorithms, such as model-based iterative reconstructions (MBIR), have demonstrated considerable success in producing high-quality reconstructions under such restrictions, but typically require high-performance computing resources with hundreds of compute nodes to solve the problem in a reasonable time. Here, tomoCAM , is introduced, a new GPU-accelerated implementation of model-based iterative reconstruction that leverages non-uniform fast Fourier transforms to efficiently compute Radon and back-projection operators and asynchronous memory transfers to maximize the throughput to the GPU memory. The resulting code is significantly faster than traditional MBIR codes and delivers the reconstructive improvement offered by MBIR with affordable computing time and resources. tomoCAM has a Python front-end, allowing access from Jupyter -based frameworks, providing straightforward integration into existing workflows at synchrotron facilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Laminography as a tool for imaging large-size samples with high resolution

Despite the increased brilliance of the new generation synchrotron sources, there is still a challenge with high-resolution scanning of very thick and absorbing samples, such as a whole mouse brain stained with heavy elements, and, extending further, brains of primates. Samples are typically cut into smaller parts, to ensure a sufficient X-ray transmission, and scanned separately. Compared with the standard tomography setup where the sample would be cut into many pillars, the laminographic geometry operates with slab-shaped sections significantly reducing the number of sample parts to be prepared, the cutting damage and data stitching problems. In this work, a laminography pipeline for imaging large samples (>1 cm) at micrometre resolution is presented. The implementation includes a low-cost instrument setup installed at the 2-BM micro-CT beamline of the Advanced Photon Source. Additionally, sample mounting, scanning techniques, data stitching procedures, a fast reconstruction algorithm with low computational complexity, and accelerated reconstruction on multi-GPU systems for processing large-scale datasets are presented. The applicability of the whole laminography pipeline was demonstrated by imaging four sequential slabs throughout an entire mouse brain sample stained with osmium, in total generating approximately 12 TB of raw data for reconstruction.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Application of Monte Carlo Algorithms to Cardiac Imaging Reconstruction

Monte Carlo algorithms have a growing impact on nuclear medicine reconstruction processes. One ofthe main limitations of myocardial perfusion imaging (MPI) is the effective mitigation of the scattering component,which is particularly challenging in Single Photon Emission Computed Tomography (SPECT). In SPECT,no timing information can be retrieved to locate the primary source photons. Monte Carlo methods allow anevent-by-event simulation of the scattering kinematics, which can be incorporated into a model of the imagingsystem response. This approach was adopted in the late Nineties by several authors, and recently took advantageof the increased computational power made available by high-performance CPUs and GPUs. These recent developmentsenable a fast image reconstruction with improved image quality, compared to deterministic approaches.Deterministic approaches are based on energy-windowing of the detector response, and on the cumulative estimateand subtraction of the scattering component. In this paper, we review the main strategies and algorithms tocorrect the scattering effect in SPECT and focus on Monte Carlo developments, which nowadays allow the threedimensionalreconstruction of SPECT cardiac images in a few seconds.

Pharmacology & Pharmacy↗
DOE OSTI2021

Algorithm-Driven Advances for Scientific CT Instruments: From model-based to deep learning-based approaches

Multiscale 3D characterization is widely used by materials scientists to further their understanding of the relationships between microscopic structure and macroscopic function. Scientific computed tomography (SCT) instruments are one of the most popular choices for 3D nondestructive characterization of materials at length scales ranging from the angstrom scale to the micron scale. These instruments typically have a source of radiation (such as electrons, X-rays, or neutrons) that interacts with the sample to be studied and a detector assembly to capture the result of this interaction (see Figure 1 ). A collection of such high-resolution measurements is made by reorienting the sample, which is mounted on a specially designed stage/holder after which reconstruction algorithms are used to produce the final 3D volume of interest. The specific choice of which instrument to use depends on the desired resolution and properties of the materials being imaged. Additionally, the end goal of SCT scans includes determining the morphology, chemical composition, or dynamic behavior of materials when subjected to external stimuli. In summary, SCT instruments are powerful tools that enable 3D characterization across multiple length scales and play a critical role in furthering the understanding of the structure–function relationships of different materials.

42 ENGINEERING↗
DOE OSTI2023

Evaluation of the Reconstruction Accuracy of the Ultrasound Model–Based Image Reconstruction (U-MBIR) Method for Concrete to Optimize Damage Detection

Reinforced concrete is a critical structural material used to construct nuclear power plants (NPPs). As such, its safety and performance must be thoroughly examined throughout the life cycle of the NPP infrastructure system. Ultrasonic measurements have been an industry standard for both surface and subsurface inspections. To support the development of these techniques, Oak Ridge National Laboratory (ORNL) has researched and developed advanced image reconstruction algorithms to capture internal damage. The results and discussion presented herein summarize the current state of the ultrasonic model–based iterative reconstruction (U-MBIR) algorithm developed at ORNL. In the work documented in this report, the U-MBIR methodology was applied to four sets of ultrasonic data collected from concrete specimens. The results demonstrate that the U-MBIR algorithm can successfully detect defects within the four concrete samples. The reconstruction images help identify the specimen thickness, regions of delamination, and location of rebar embedded within the concrete. The reconstruction images allow engineers and technicians to characterize the internal defects within concrete specimens and structural members. Ultimately, this knowledge can guide engineers in making informed decisions regarding the performance, safety, and reliability of structural materials (i.e., reinforced concrete) throughout the life cycle of NPPs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Supernova electron-neutrino interactions with xenon in the nEXO detector

Electron-neutrino charged-current interactions with xenon nuclei were modeled in the nEXO neutrinoless double-𝛽 decay detector (∼5 metric ton, 90% 136 Xe, 10% 134 Xe) to evaluate its sensitivity to supernova neutrinos. Predictions for event rates and detectable signatures were modeled using the Model of Argon Reaction Low Energy Yields (MARLEY) event generator. We find good agreement between MARLEY’s predictions and existing theoretical calculations of the inclusive cross sections at supernova neutrino energies. The interactions modeled by MARLEY were simulated within the nEXO simulation framework and were run through an example reconstruction algorithm to determine the detector’s efficiency for reconstructing these events. The simulated data, incorporating the detector response, were used to study the ability of nEXO to reconstruct the incident electron-neutrino spectrum and these results were extended to a larger xenon detector of the same isotope enrichment. We estimate that nEXO will be able to observe electron-neutrino interactions with xenon from supernovae as far as 5–8 kpc from Earth, while the ability to reconstruct incident electron-neutrino spectrum parameters from observed interactions in nEXO is limited to closer supernovae.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗