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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Eucalyptus – An Analysis Suite for Fault Trees with Uncertainty Quantification

Eucalyptus is a novel code developed at Lawrence Livermore National Laboratory to incorporate uncertainty quantification into Fault Tree Analysis (FTA). This tool addresses the challenge of imperfect knowledge in “grey-box” systems by allowing analysts to incorporate and propagate uncertainty from component-level assessments to system-level effects. Eucalyptus facilitates a consistent evaluation of the impact of subject matter expert judgment and knowledge gaps on overall system response by Monte Carlo generation of possible system fault trees, sampling probabilities of the existence of subsystems and components. Here, the code supports the specification of fault trees through text and allows export to various formats, including auto-generated images, easing analysis and reducing errors. It has undergone extensive verification testing, demonstrating its reliability and readiness for deployment, and leverages on-node parallelism for rapid analysis. Example analyses are shown that include the identification of system failure paths and quantification of the value of further information about system components.

Fault Tree Analysis↗
DOE OSTI2026

SimLBR: Learning to Detect Fake Images by Learning to Detect Real Images

The rapid advancement of generative models has made the detection of AI-generated images a critical challenge for both research and society. Recent works have shown that most state-of-the-art fake image detection methods overfit to their training data and catastrophically fail when evaluated on curated hard test sets with strong distribution shifts. In this work, we argue that it is more principled to learn a tight decision boundary around the real image distribution and treat the fake category as a sink class. To this end, we propose SimLBR, a simple and efficient framework for fake image detection with Latent Blending Regularization (LBR). Our method significantly improves cross-generator generalization, achieving up to +24.85% accuracy and +69.62% recall on the challenging Chameleon benchmark. SimLBR is also highly efficient, training orders of magnitude faster than existing approaches. Furthermore, we emphasize the need for reliability-oriented evaluation in fake image detection, introducing risk-adjusted metrics and worst-case estimates to better assess model robustness. All the code and models are availabe at: https://github.com/mvrl/SimLBR

Dhakal, Aayush [Washington University, St. Louis]↗
DOE OSTI2016

SU-D-206-02: Evaluation of Partial Storage of the System Matrix for Cone Beam Computed Tomography Using a GPU Platform

Purpose: Iterative reconstruction algorithms in computed tomography (CT) require a fast method for computing the intersections between the photons’ trajectories and the object, also called ray-tracing or system matrix computation. This work evaluates different ways to store the system matrix, aiming to reconstruct dense image grids in reasonable time. Methods: We propose an optimized implementation of the Siddon’s algorithm using graphics processing units (GPUs) with a novel data storage scheme. The algorithm computes a part of the system matrix on demand, typically, for one projection angle. The proposed method was enhanced with accelerating options: storage of larger subsets of the system matrix, systematic reuse of data via geometric symmetries, an arithmetic-rich parallel code and code configuration via machine learning. It was tested on geometries mimicking a cone beam CT acquisition of a human head. To realistically assess the execution time, the ray-tracing routines were integrated into a regularized Poisson-based reconstruction algorithm. The proposed scheme was also compared to a different approach, where the system matrix is fully pre-computed and loaded at reconstruction time. Results: Fast ray-tracing of realistic acquisition geometries, which often lack spatial symmetry properties, was enabled via the proposed method. Ray-tracing interleaved with projection and backprojection operations required significant additional time. In most cases, ray-tracing was shown to use about 66 % of the total reconstruction time. In absolute terms, tracing times varied from 3.6 s to 7.5 min, depending on the problem size. The presence of geometrical symmetries allowed for non-negligible ray-tracing and reconstruction time reduction. Arithmetic-rich parallel code and machine learning permitted a modest reconstruction time reduction, in the order of 1 %. Conclusion: Partial system matrix storage permitted the reconstruction of higher 3D image grid sizes and larger projection datasets at the cost of additional time, when compared to the fully pre-computed approach. This work was supported in part by the Fonds de recherche du Quebec - Nature et technologies (FRQ-NT). The authors acknowledge partial support by the CREATE Medical Physics Research Training Network grant of the Natural Sciences and Engineering Research Council of Canada (Grant No. 432290).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-CD-207B-11: Multi-Vendor Phantom Study of CT Lung Density Metrics: Is a Reproducibility of Less Than 1 HU Achievable?

Purpose: To standardize the calibration procedures of CT lung density measurements using low-density reference foams in a phantom, and to demonstrate a reproducibility of less than 1 HU for lung equivalent foam densities measured across CT vendor platforms and protocols. Methods: A phantom study was conducted on CT scanner models from 4 vendors at 100, 120, and 135/140 kVp and 1.5, 3, and 6 mGy dose settings, using a lung density phantom containing air, water, and 3 reference foams (indirectly calibrated) with discrete densities simulating a 5-cm slice of the human chest. Customized segmentation software was used to analyze the images and generate a mean HU and variance for each of the density for the 22 vendor/protocols. A 3-step calibration process was devised to remove a scanner-dependent parameter using linear regression of the HU value vs the relative electron density. The results were mapped to a single energy (80 keV) for final comparison. Results: The heterogeneity across vendor platforms for each density assessed by a random effects model was reduced by 50% after re-calibration, while the standard deviation of the mean HU values also improved by about the same amount. The 95% CI of the final HU value was within +/−1 HU for all 3 reference foam densities. For the backing lung foam in the phantom (served as an “unknown”), this CI is +/− 1.6 HU. The kVp and dose settings did not appear to have significant contributions to the variability. Conclusion: With the proposed calibration procedures, the inter-scanner reproducibility of better than 1 HU is demonstrated in the current phantom study for the reference foam densities, but not yet achieved for a test density. The sources of error are being investigated in the next round of scanning with a certified Standard Reference Material for direct calibration. Fain: research funding from GE Healthcare to develop pulmonary MRI techniques. Hoppel: employee of Toshiba Medical Research Institute USA/financial interest with GE Healthcare. M. Fuld: employee of Siemens Healthcare for medical device equipment and software. This project is supported partially by RSNA QIBA Concept Award (Fain), NIH/NIBIB, HHSN268201300071C (Y).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-145: Validation of An Analytical Model for in Vivo Range Verification Using GATE Monte Carlo Simulation in Proton Therapy

Purpose: Predicted PET images on the basis of analytical filtering approach for proton range verification has been successful developed and validated using FLUKA Monte Carlo (MC) codes and phantom measurements. The purpose of the study is to validate the effectiveness of analytical filtering model for proton range verification on GATE/GEANT4 Monte Carlo simulation codes. Methods: In this study, we performed two experiments for validation of predicted β+-isotope by the analytical model with GATE/GEANT4 simulations. The first experiments to evaluate the accuracy of predicting β+-yields as a function of irradiated proton energies. In second experiment, we simulate homogeneous phantoms of different materials irradiated by a mono-energetic pencil-like proton beam. The results of filtered β+-yields distributions by the analytical model is compared with those of MC simulated β+-yields in proximal and distal fall-off ranges. Results: The results investigate the distribution between filtered β+-yields and MC simulated β+-yields distribution in different conditions. First, we found that the analytical filtering can be applied over the whole range of the therapeutic energies. Second, the range difference between filtered β+-yields and MC simulated β+-yields at the distal fall-off region are within 1.5mm for all materials used. The findings validated the usefulness of analytical filtering model on range verification of proton therapy on GATE Monte Carlo simulations. In addition, there is a larger discrepancy between filtered prediction and MC simulated β+-yields using GATE code, especially in proximal region. This discrepancy might Result from the absence of wellestablished theoretical models for predicting the nuclear interactions. Conclusion: Despite the fact that large discrepancies of the distributions between MC-simulated and predicted β+-yields were observed, the study prove the effectiveness of analytical filtering model for proton range verification using GATE Monte Carlo simulation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Obtain3D_open

This computer code uses the concept of the parallax to compute the x, y and z coordinates of points found using transmission electron microscopy (TEM), or any transmission imaging technique, using two images, each taken at a different perspective of the region containing the points. Points correspond, but are not limited, to the center of cavities or precipitates, positions of irradiation black dot damage, positions along a dislocation line, or positions along where an interface meets a free surface. Features can include dislocations, interfaces, cavities, precipitates, inclusions etc. The x, y and z coordinates of the points are output in a text file. The code also allows the user to visualize the features containing the points in three dimensions.

Eftink, Benjamin↗
DOE OSTI2021

Full-field imaging learning machine (FILM)

A method of determining dynamic properties of a structure (linear or nonlinear) includes receiving spatio-temporal inputs, generating mode shapes and modal components corresponding to the spatio-temporal inputs using a trained deep complexity coding artificial neural network, and subsequently generating the dynamic properties by analyzing each modal component using a trained learning machine. A computing system for non-contact determination of dynamic properties of a structure includes a camera, a processor, and a memory including computer-executable instructions. When the instructions are executed, the system is caused to receive spatio-temporal image data, decompose the spatio-temporal image data into constituent manifold components using an autoencoder, and analyze the constituent manifold components using a trained learning machine to determine the dynamic properties.

Yang, Yongchao↗
DOE OSTI2013

A Mobile Automated Tomographic Gamma Scanning System - 13231

Canberra Industries have recently designed and built a new automated Tomographic Gamma Scanning (TGS) system for mobile deployment. The TGS technique combines high-resolution gamma spectroscopy with low spatial resolution 3-dimensional image reconstruction to provide increased accuracy over traditional approaches for the assay of non-uniform source distributions in low-to medium-density, non-heterogeneous matrices. Originally pioneered by R. Estep at Los Alamos National Laboratory (LANL), the TGS method has been further developed and commercialized by Canberra Industries in recent years. The present system advances the state of the art on several fronts: it is designed to be housed in a standard cargo transport container for ease of transport, allowing waste characterization at multiple facilities under the purview of a single operator. Conveyor feed, drum rotator, and detector and collimator positioning mechanisms operated by programmable logic control (PLC) allow automated batch mode operation. The variable geometry settings can accommodate a wide range of waste packaging, including but not limited to standard 220 liter drums, 380 liter overpack drums, and smaller 20 liter cans. A 20 mCi Eu-152 transmission source provides attenuation corrections for drum matrices up to 1 g/cm{sup 3} in TGS mode; the system can be operated in Segmented Gamma Scanning (SGS) mode to measure higher density drums. To support TGS assays at higher densities, the source shield is sufficient to house an alternate Co-60 transmission source of higher activity, up to 250 mCi. An automated shutter and attenuator assembly is provided for operating the system with a dual intensity transmission source. The system's 1500 kg capacity rotator turntable can handle heavy containers such as concrete lined 380 liter overpack drums. Finally, data acquisition utilizes Canberra's Broad Energy Germanium (BEGE) detector and Lynx MCA, with 32 k channels, providing better than 0.1 keV/channel resolution to support both isotopic analysis with the MGA/MGAU software and a wide 3 MeV dynamic range. The calibration and verification of the system is discussed, and quantitative results are presented for a variety of drum types and matrices. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Coarse-to-fine Task-driven Inpainting for Geoscience Images

The processing and recognition of geoscience images have wide applications. Most of existing researches focus on understanding the high-quality geoscience images by assuming that all the images are clear. However, in many real-world cases, the geoscience images might contain occlusions during the image acquisition. This problem actually implies the image inpainting problem in computer vision and multimedia. As far as we know, all the existing image inpainting algorithms learn to repair the occluded regions for a better visualization quality, they are excellent for natural images but not good enough for geoscience images, and they never consider the following geoscience task when developing inpainting methods. Here, this paper aims to repair the occluded regions for a better geoscience task performance and advanced visualization quality simultaneously, without changing the current deployed deep learning based geoscience models. Because of the complex context of geoscience images, we propose a coarse-to-fine encoder-decoder network with the help of designed coarse-to-fine adversarial context discriminators to reconstruct the occluded image regions. Due to the limited data of geoscience images, we propose a MaskMix based data augmentation method, which augments inpainting masks instead of augmenting original images, to exploit the limited geoscience image data. The experimental results on three public geoscience datasets for remote sensing scene recognition, cross-view geolocation and semantic segmentation tasks respectively show the effectiveness and accuracy of the proposed method. The code is available at: https://github.com/HMS97/Task-driven-Inpainting.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Improved proton computed tomography by dual modality image reconstruction

Purpose: Proton computed tomography (CT) is a promising image modality for improving the stopping power estimates and dose calculations for particle therapy. However, the finite range of about 33 cm of water of most commercial proton therapy systems limits the sites that can be scanned from a full 360° rotation. In this paper the authors propose a method to overcome the problem using a dual modality reconstruction (DMR) combining the proton data with a cone-beam x-ray prior. Methods: A Catphan 600 phantom was scanned using a cone beam x-ray CT scanner. A digital replica of the phantom was created in the Monte Carlo code Geant4 and a 360° proton CT scan was simulated, storing the entrance and exit position and momentum vector of every proton. Proton CT images were reconstructed using a varying number of angles from the scan. The proton CT images were reconstructed using a constrained nonlinear conjugate gradient algorithm, minimizing total variation and the x-ray CT prior while remaining consistent with the proton projection data. The proton histories were reconstructed along curved cubic-spline paths. Results: The spatial resolution of the cone beam CT prior was retained for the fully sampled case and the 90° interval case, with the MTF = 0.5 (modulation transfer function) ranging from 5.22 to 5.65 linepairs/cm. In the 45° interval case, the MTF = 0.5 dropped to 3.91 linepairs/cm For the fully sampled DMR, the maximal root mean square (RMS) error was 0.006 in units of relative stopping power. For the limited angle cases the maximal RMS error was 0.18, an almost five-fold improvement over the cone beam CT estimate. Conclusions: Dual modality reconstruction yields the high spatial resolution of cone beam x-ray CT while maintaining the improved stopping power estimation of proton CT. In the case of limited angles, the use of prior image proton CT greatly improves the resolution and stopping power estimate, but does not fully achieve the quality of a 360° proton CT scan.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

An ultra-fast method for generating synthetic down-scattered neutron data for inertial confinement fusion implosions

In inertial confinement fusion experiments at the National Ignition Facility, asymmetries are probed by a variety of neutron diagnostics, including neutron imaging systems, real-time neutron activation diagnostics (RTNADs), and neutron spectrometers. It is often useful to generate synthetic data based on these diagnostics to validate and tune models. However, current methods of doing so using Monte Carlo particle tracing are time-consuming. In this paper, an ultra-fast method is presented for generating synthetic neutron images, RTNAD data, and spectrometry data using line integrals and 3D convolutions. While it does not contain as much physics as particle tracing codes, it is thousands of times faster and produces nearly identical data. This enables analysis techniques that depend on generating large amounts of synthetic data, which will prove very useful for the study of asymmetries going forward.

Deuterium↗
DOE OSTI2021

edxia: Microstructure characterisation from quantified SEM-EDS hypermaps

The characterisation of cement paste microstructure is an important step towards understanding durability mechanisms in cementitious materials. Scanning electron microscopy (SEM) coupled with energy dispersive spectroscopy (EDS) is a widely used technique to analyse the microstructure at the micron-scale. However, it is challenging, notably because the characteristic size of many phases is found on a scale smaller than the EDS interaction volume. This work presents a new image analysis framework to identify phases and quantify the microstructure of cementitious materials from SEM-EDS hypermaps. By leveraging domain knowledge, representative points are attributed to phases and mixtures of phases based on ratio plots. Then, quantitative analysis of the microstructure can be carried out (chemical composition, particle size distributions, volume fractions, …). We demonstrate the abilities of the framework, and we present possible applications and extensions of the method. The framework is available as both a graphical interface and a Python code.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Designing symmetric polar direct drive implosions on the Omega laser facility

Achieving symmetric capsule implosions with Polar Direct Drive [S. Skupsky et al., Phys. Plasmas 11, 2763 (2004); R. S. Craxton et al., Phys. Plasmas 12, 056304 (2005); F. J. Marshall et al., J. Phys. IV France 133, 153–157 (2006)] has been explored during recent Defect Induced Mix Experiment campaign on the Omega facility at the Laboratory for Laser Energetics. To minimize the implosion asymmetry due to laser drive, optimized laser cone powers, as well as improved beam pointings, were designed using 3D radiation-hydrodynamics code HYDRA [M. M. Marinak et al., Phys. Plasmas 3, 2070 (1996)]. Experimental back-lit radiographic and self-emission images revealed improved polar symmetry and increased neutron yield which were in good agreement with 2D HYDRA simulations. In particular, by reducing the energy in Omega's 21.4° polar rings by 16.75%, while increasing the energy in the 58.9° equatorial rings by 8.25% in such a way as to keep the overall energy to the target at 16 kJ, the second Legendre mode (P{sub 2}) was reduced by a factor of 2, to less than 4% at bang time. At the same time the neutron yield increased by 62%. The polar symmetry was also improved relative to nominal DIME settings by a more radical repointing of OMEGA's 42.0° and 58.9° degree beams, to compensate for oblique incidence and reduced absorption at the equator, resulting in virtually no P{sub 2} around bang time and 33% more yield.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

unWISE: Unblurred coadds of the WISE imaging

The Wide-field Infrared Survey Explorer (WISE) satellite observed the full sky in four mid-infrared bands in the 2.8-28 μm range. The primary mission was completed in 2010. The WISE team has done a superb job of producing a series of high-quality, well-documented, complete data releases in a timely manner. However, the 'Atlas Image' coadds that are part of the recent AllWISE and previous data releases were intentionally blurred. Convolving the images by the point-spread function while coadding results in 'matched-filtered' images that are close to optimal for detecting isolated point sources. But these matched-filtered images are sub-optimal or inappropriate for other purposes. For example, we are photometering the WISE images at the locations of sources detected in the Sloan Digital Sky Survey through forward modeling, and this blurring decreases the available signal-to-noise by effectively broadening the point-spread function. This paper presents a new set of coadds of the WISE images that have not been blurred. These images retain the intrinsic resolution of the data and are appropriate for photometry preserving the available signal-to-noise. Users should be cautioned, however, that the W3- and W4-band coadds contain artifacts around large, bright structures (large galaxies, dusty nebulae, etc.); eliminating these artifacts is the subject of ongoing work. These new coadds, and the code used to produce them, are publicly available at http://unwise.me.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Experimental Investigation on Metallic Droplet Behavior in Molten BOF Slag

In order to better understand the metallic droplet behavior during a slag treatment process, a physical modeling based on the similarity principle was performed in a transparent scaled-down vessel at room temperature. Paraffin oil, 20 wt pct copper sulfate solution, and compressed air were used to simulate the molten slag, metallic droplet, and carrier gas, respectively. The droplets injected into paraffin oil during the experiment were captured by a high speed camera and were analyzed by Image Pro Plus software to obtain the droplet size distribution. The critical droplet size in the physical modeling and slag treatment process is quantitatively correlated. The results show that droplet breakage phenomenon is dominant over its coalescence in the current industrial practice, and droplet breakage is enhanced with increasing gas flow rate and/or lance depth. No significant effect of the nozzle configuration was found on the droplet breakage and coalescence. The droplet size distribution varies with the lance position. Gas flow rate and lance depth are the most important factors for droplet breakage, the extent of which can be reduced through a proper selection of the operational conditions. A linear relationship between the droplet size and the input energy flux is obtained.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Optics of the NIFS negative ion source test stand by infrared calorimetry and numerical modelling

At National Institute for Fusion Science (NIFS), a multi-ampere negative ion source is used to support the R&D on H{sup −} production, extraction, and acceleration. In this contribution, we study the characteristics of the acceleration system of this source, in order to characterize the beam optics at different operational conditions. A dedicated experimental campaign was carried out at NIFS, using as main diagnostic the infra-red imaging of the beam profiles. The experimental measurements are also compared with 3D numerical simulations, in order to validate the codes and to assess their degree of reliability. The simulations show a satisfactory agreement with the experimental results.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Concept Lens: Visual Comparison and Evaluation of Generative Model Manipulations

Generative models are becoming a transformative technology for the creation and editing of images. However, it remains challenging to harness these models for precise image manipulation. These challenges often manifest as inconsistency in the editing process, where both the type and amount of semantic change, depend on the image being manipulated. Moreover, there exist many methods for computing image manipulations, whose development is hindered by the matter of inconsistency. This paper aims to address these challenges by improving how we evaluate, compare, and explore the space of manipulations offered by a generative model. We present Concept Lens, a visual interface that is designed to aid users in understanding semantic concepts carried in image manipulations, and how these manipulations vary over generated images. Given the large space of possible images produced by a generative model, Concept Lens is designed to support the exploration of both generated images, and their manipulations, at multiple levels of detail. To this end, the layout of Concept Lens is informed by two hierarchies: a hierarchical organization of (1) original images, grouped by their similarities, and (2) image manipulations, where manipulations that induce similar changes are grouped together. This layout allows one to discover the types of images that consistently respond to a group of manipulations, and vice versa, manipulations that consistently respond to a group of codes. We show the benefits of this design across multiple use cases, specifically, studying the quality of manipulations for a single method, and offering a means of comparing different methods.

clustering↗
DOE OSTI2012

Fast patient-specific Monte Carlo brachytherapy dose calculations via the correlated sampling variance reduction technique

Purpose: To demonstrate potential of correlated sampling Monte Carlo (CMC) simulation to improve the calculation efficiency for permanent seed brachytherapy (PSB) implants without loss of accuracy. Methods: CMC was implemented within an in-house MC code family (PTRAN) and used to compute 3D dose distributions for two patient cases: a clinical PSB postimplant prostate CT imaging study and a simulated post lumpectomy breast PSB implant planned on a screening dedicated breast cone-beam CT patient exam. CMC tallies the dose difference, {Delta}D, between highly correlated histories in homogeneous and heterogeneous geometries. The heterogeneous geometry histories were derived from photon collisions sampled in a geometrically identical but purely homogeneous medium geometry, by altering their particle weights to correct for bias. The prostate case consisted of 78 Model-6711 {sup 125}I seeds. The breast case consisted of 87 Model-200 {sup 103}Pd seeds embedded around a simulated lumpectomy cavity. Systematic and random errors in CMC were unfolded using low-uncertainty uncorrelated MC (UMC) as the benchmark. CMC efficiency gains, relative to UMC, were computed for all voxels, and the mean was classified in regions that received minimum doses greater than 20%, 50%, and 90% of D{sub 90}, as well as for various anatomical regions. Results: Systematic errors in CMC relative to UMC were less than 0.6% for 99% of the voxels and 0.04% for 100% of the voxels for the prostate and breast cases, respectively. For a 1 x 1 x 1 mm{sup 3} dose grid, efficiency gains were realized in all structures with 38.1- and 59.8-fold average gains within the prostate and breast clinical target volumes (CTVs), respectively. Greater than 99% of the voxels within the prostate and breast CTVs experienced an efficiency gain. Additionally, it was shown that efficiency losses were confined to low dose regions while the largest gains were located where little difference exists between the homogeneous and heterogeneous doses. On an AMD 1090T processor, computing times of 38 and 21 sec were required to achieve an average statistical uncertainty of 2% within the prostate (1 x 1 x 1 mm{sup 3}) and breast (0.67 x 0.67 x 0.8 mm{sup 3}) CTVs, respectively. Conclusions: CMC supports an additional average 38-60 fold improvement in average efficiency relative to conventional uncorrelated MC techniques, although some voxels experience no gain or even efficiency losses. However, for the two investigated case studies, the maximum variance within clinically significant structures was always reduced (on average by a factor of 6) in the therapeutic dose range generally. CMC takes only seconds to produce an accurate, high-resolution, low-uncertainly dose distribution for the low-energy PSB implants investigated in this study.

61 RADIATION PROTECTION AND DOSIMETRY↗