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At least 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

MO-DE-207A-09: Low-Dose CT Image Reconstruction Via Learning From Different Patient Normal-Dose Images

Purpose: To investigate a novel low-dose CT (LdCT) image reconstruction strategy for lung CT imaging in radiation therapy. Methods: The proposed approach consists of four steps: (1) use the traditional filtered back-projection (FBP) method to reconstruct the LdCT image; (2) calculate structure similarity (SSIM) index between the FBP-reconstructed LdCT image and a set of normal-dose CT (NdCT) images, and select the NdCT image with the highest SSIM as the learning source; (3) segment the NdCT source image into lung and outside tissue regions via simple thresholding, and adopt multiple linear regression to learn high-order Markov random field (MRF) pattern for each tissue region in the NdCT source image; (4) segment the FBP-reconstructed LdCT image into lung and outside regions as well, and apply the learnt MRF prior in each tissue region for statistical iterative reconstruction of the LdCT image following the penalized weighted least squares (PWLS) framework. Quantitative evaluation of the reconstructed images was based on the signal-to-noise ratio (SNR), local binary pattern (LBP) and histogram of oriented gradients (HOG) metrics. Results: It was observed that lung and outside tissue regions have different MRF patterns predicted from the NdCT. Visual inspection showed that our method obviously outperformed the traditional FBP method. Comparing with the region-smoothing PWLS method, our method has, in average, 13% increase in SNR, 15% decrease in LBP difference, and 12% decrease in HOG difference from reference standard for all regions of interest, which indicated the superior performance of the proposed method in terms of image resolution and texture preservation. Conclusion: We proposed a novel LdCT image reconstruction method by learning similar image characteristics from a set of NdCT images, and the to-be-learnt NdCT image does not need to be scans from the same subject. This approach is particularly important for enhancing image quality in radiation therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

DECONVOLUTION OF IMAGES FROM BLAST 2005: INSIGHT INTO THE K3-50 AND IC 5146 STAR-FORMING REGIONS

We present an implementation of the iterative flux-conserving Lucy-Richardson (L-R) deconvolution method of image restoration for maps produced by the Balloon-borne Large Aperture Submillimeter Telescope (BLAST). Compared to the direct Fourier transform method of deconvolution, the L-R operation restores images with better-controlled background noise and increases source detectability. Intermediate iterated images are useful for studying extended diffuse structures, while the later iterations truly enhance point sources to near the designed diffraction limit of the telescope. The L-R method of deconvolution is efficient in resolving compact sources in crowded regions while simultaneously conserving their respective flux densities. We have analyzed its performance and convergence extensively through simulations and cross-correlations of the deconvolved images with available high-resolution maps. We present new science results from two BLAST surveys, in the Galactic regions K3-50 and IC 5146, further demonstrating the benefits of performing this deconvolution. We have resolved three clumps within a radius of 4.'5 inside the star-forming molecular cloud containing K3-50. Combining the well-resolved dust emission map with available multi-wavelength data, we have constrained the spectral energy distributions (SEDs) of five clumps to obtain masses (M), bolometric luminosities (L), and dust temperatures (T). The L-M diagram has been used as a diagnostic tool to estimate the evolutionary stages of the clumps. There are close relationships between dust continuum emission and both 21 cm radio continuum and {sup 12}CO molecular line emission. The restored extended large-scale structures in the Northern Streamer of IC 5146 have a strong spatial correlation with both SCUBA and high-resolution extinction images. A dust temperature of 12 K has been obtained for the central filament. We report physical properties of ten compact sources, including six associated protostars, by fitting SEDs to multi-wavelength data. All of these compact sources are still quite cold (typical temperature below {approx} 16 K) and are above the critical Bonner-Ebert mass. They have associated low-power young stellar objects. Further evidence for starless clumps has also been found in the IC 5146 region.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

A Reinforcement Learning Approach to Parameter Selection for Distributed Optimal Power Flow

With the increasing penetration of distributed energy resources, distributed optimization algorithms have attracted significant attention for power systems applications due to their potential for superior scalability, privacy, and robustness to a single point-of-failure. The Alternating Direction Method of Multipliers (ADMM) is a popular distributed optimization algorithm; however, its convergence performance is highly dependent on the selection of penalty parameters, which are usually chosen heuristically. In this work, we use reinforcement learning (RL) to develop an adaptive penalty parameter selection policy for alternating current optimal power flow (ACOPF) problem solved via ADMM with the goal of minimizing the number of iterations until convergence. We train our RL policy using deep Q-learning and show that this policy can result in significantly accelerated convergence (up to a 59% reduction in the number of iterations compared to existing, curvatureinformed penalty parameter selection methods). Furthermore, we show that our RL policy demonstrates promise for generalizability, performing well under unseen loading schemes as well as under unseen losses of lines and generators (up to a 50% reduction in iterations). This work thus provides a proof-of-concept for using RL for parameter selection in ADMM for power systems applications.

alternating current optimal power flow↗
DOE OSTI2010

Statistical shape model-based reconstruction of a scaled, patient-specific surface model of the pelvis from a single standard AP x-ray radiograph

Purpose: The aim of this article is to investigate the feasibility of using a statistical shape model (SSM)-based reconstruction technique to derive a scaled, patient-specific surface model of the pelvis from a single standard anteroposterior (AP) x-ray radiograph and the feasibility of estimating the scale of the reconstructed surface model by performing a surface-based 3D/3D matching. Methods: Data sets of 14 pelvises (one plastic bone, 12 cadavers, and one patient) were used to validate the single-image based reconstruction technique. This reconstruction technique is based on a hybrid 2D/3D deformable registration process combining a landmark-to-ray registration with a SSM-based 2D/3D reconstruction. The landmark-to-ray registration was used to find an initial scale and an initial rigid transformation between the x-ray image and the SSM. The estimated scale and rigid transformation were used to initialize the SSM-based 2D/3D reconstruction. The optimal reconstruction was then achieved in three stages by iteratively matching the projections of the apparent contours extracted from a 3D model derived from the SSM to the image contours extracted from the x-ray radiograph: Iterative affine registration, statistical instantiation, and iterative regularized shape deformation. The image contours are first detected by using a semiautomatic segmentation tool based on the Livewire algorithm and then approximated by a set of sparse dominant points that are adaptively sampled from the detected contours. The unknown scales of the reconstructed models were estimated by performing a surface-based 3D/3D matching between the reconstructed models and the associated ground truth models that were derived from a CT-based reconstruction method. Such a matching also allowed for computing the errors between the reconstructed models and the associated ground truth models. Results: The technique could reconstruct the surface models of all 14 pelvises directly from the landmark-based initialization. Depending on the surface-based matching techniques, the reconstruction errors were slightly different. When a surface-based iterative affine registration was used, an average reconstruction error of 1.6 mm was observed. This error was increased to 1.9 mm, when a surface-based iterative scaled rigid registration was used. Conclusions: It is feasible to reconstruct a scaled, patient-specific surface model of the pelvis from single standard AP x-ray radiograph using the present approach. The unknown scale of the reconstructed model can be estimated by performing a surface-based 3D/3D matching.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

SU-E-J-69: Iterative Deconvolution of the Initial Photon Fluence for EPID Dosimetry: A Monte Carlo Based Study

Purpose: Developing a fast and accurate calculation model to reconstruct the applied photon fluence from an external photon radiation therapy treatment based on an image recorded by an electronic portal image device (EPID). Methods: To reconstruct the initial photon fluence the 2D EPID image was corrected for scatter from the patient/phantom and EPID to generate the transmitted primary photon fluence. This was done by an iterative deconvolution using precalculated point spread functions (PSF). The transmitted primary photon fluence was then backprojected through the patient/phantom geometry considering linear attenuation to receive the initial photon fluence applied for the treatment.The calculation model was verified using Monte Carlo simulations performed with the EGSnrc code system. EPID images were produced by calculating the dose deposition in the EPID from a 6 MV photon beam irradiating a water phantom with air and bone inhomogeneities and the ICRP anthropomorphic voxel phantom. Results: The initial photon fluence was reconstructed using a single PSF and position dependent PSFs which depend on the radiological thickness of the irradiated object. Appling position dependent point spread functions the mean uncertainty of the reconstructed initial photon fluence could be reduced from 1.13 % to 0.13 %. Conclusion: This study presents a calculation model for fluence reconstruction from EPID images. The{sup Result} show a clear advantage when position dependent PSF are used for the iterative reconstruction. The basic work of a reconstruction method was established and further evaluations must be made in an experimental study.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Clinical evaluation of the iterative metal artifact reduction algorithm for CT simulation in radiotherapy

Purpose: To clinically evaluate an iterative metal artifact reduction (IMAR) algorithm prototype in the radiation oncology clinic setting by testing for accuracy in CT number retrieval, relative dosimetric changes in regions affected by artifacts, and improvements in anatomical and shape conspicuity of corrected images. Methods: A phantom with known material inserts was scanned in the presence/absence of metal with different configurations of placement and sizes. The relative change in CT numbers from the reference data (CT with no metal) was analyzed. The CT studies were also used for dosimetric tests where dose distributions from both photon and proton beams were calculated. Dose differences and gamma analysis were calculated to quantify the relative changes between doses calculated on the different CT studies. Data from eight patients (all different treatment sites) were also used to quantify the differences between dose distributions before and after correction with IMAR, with no reference standard. A ranking experiment was also conducted to analyze the relative confidence of physicians delineating anatomy in the near vicinity of the metal implants. Results: IMAR corrected images proved to accurately retrieve CT numbers in the phantom study, independent of metal insert configuration, size of the metal, and acquisition energy. For plastic water, the mean difference between corrected images and reference images was −1.3 HU across all scenarios (N = 37) with a 90% confidence interval of [−2.4, −0.2] HU. While deviations were relatively higher in images with more metal content, IMAR was able to effectively correct the CT numbers independent of the quantity of metal. Residual errors in the CT numbers as well as some induced by the correction algorithm were found in the IMAR corrected images. However, the dose distributions calculated on IMAR corrected images were closer to the reference data in phantom studies. Relative spatial difference in the dose distributions in the regions affected by the metal artifacts was also observed in patient data. However, in absence of a reference ground truth (CT set without metal inserts), these differences should not be interpreted as improvement/deterioration of the accuracy of calculated dose. With limited data presented, it was observed that proton dosimetry was affected more than photons as expected. Physicians were significantly more confident contouring anatomy in the regions affected by artifacts. While site specific preferences were detected, all indicated that they would consistently use IMAR corrected images. Conclusions: IMAR correction algorithm could be readily implemented in an existing clinical workflow upon commercial release. While residual errors still exist in IMAR corrected images, these images present with better overall conspicuity of the patient/phantom geometry and offer more accurate CT numbers for improved local dosimetry. The variety of different scenarios included herein attest to the utility of the evaluated IMAR for a wide range of radiotherapy clinical scenarios.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Data-driven linear time advance operators for the acceleration of plasma physics simulation

In this study, we demonstrate the application of data-driven linear operator construction for time advance with a goal of accelerating plasma physics simulation. We apply dynamic mode decomposition (DMD) to data produced by the nonlinear SOLPS-ITER (Scrape-off Layer Plasma Simulator - International Thermonuclear Experimental Reactor) plasma boundary code suite in order to estimate a series of linear operators and monitor their predictive accuracy via online error analysis. We find that this approach defines when these dynamics can be represented by a sequence of approximate linear operators and is essential for providing consistent projections when compared to an unconstrained application. For linear diffusion and advection–diffusion fluid test problems, we construct and apply operators within explicit and implicit time advance schemes, demonstrating that stability can be robustly guaranteed in each case. We further investigate the use of the linear time advance operators within several integration methods including forward Euler, backward Euler, and the matrix exponential. The application of this method to simulation data from SOLPS-ITER, with varying levels of Markov chain Monte Carlo numerical noise, shows that constrained DMD operators yield a capability to identify, extract, and integrate a (slow) subset of the present timescales. Example applications show that for projected speedup factors of [Formula: see text], and [Formula: see text], a mean relative error of 3%, 5%, and 8% and maximum relative error less than 20% are achievable, which appears acceptable for typical SOLPS-ITER steady-state simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

TU-F-CAMPUS-I-02: Contrast Enhanced Cone Beam CT Imaging with Dual- Gantry Image Acquisition and Constrained Iterative Reconstruction-a Simulation Study for Liver Imaging Application

Purpose: Contrast time-density curves may help differentiate malignant tumors from normal tissues or benign tumors. Repetitive scans using conventional CT or cone beam CT techniques, which Result in unacceptably high dose, may not achieve the desired temporal resolution. In this study we describe and demonstrate a 4D imaging technique for imaging and quantifying contrast flows requiring only one or two 360° scans. Methods: A dual-gantry system is used to simultaneously acquire two projection images at orthogonal orientations. Following the scan, each or both of the two 360° projection sets are used to reconstruct an average contrast enhanced image set which is then segmented to form a 3D contrast map. Alternatively, a pre-injection scan may be made and used to reconstruct a pre-injection image set which is subtracted from the post-injection image set to form the 3D contrast map. Each of the two 360° projection sets is divided into 12 subsets, thus creating 12 pairs of 30° limited angle projection sets, each corresponding to a time spanning over 1/12 of the scanning time. Each pair of the projection sets are reconstructed as a time specific 3D image set with the maximum likelihood estimation iterative algorithm using the contrast map as the constraint. As a demonstration, a 4D abdominal phantom was constructed from clinical CT images with blood flow through the normal tissue and a tumor modeled and imaging process simulated. Results: We have successfully generated a 4D image phantom, and calculated the projection images. The time density curves derived from the reconstructed image set matched well with the flow model used to generate the phantom. Conclusion: Dual-gantry image acquisition and constrained iterative reconstruction algorithm may help to obtain time-density curves of contrast agents in blood flows, which may help differentiate malignant tumors from normal tissues or benign tumors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-204: Improving Multiple Isocenter Coincidence: Elekta Beam Modulator with HexaPOD Six Degrees Couchtop

Purpose: With evolution from frame-based to image-guided SRS/SRT technique, the coincidence of multiple isocenters must be within a tight tolerance: MV, kV, table mechanical, and, in this case, HexaPOD 6° patient positioning system. Reported here is a method for improving the effectiveness of an isocenter alignment procedure which ultimately led to isocenter coincidence on an Elekta Beam Modulator LINAC equipped with 4 mm MLC leaves and a fixed secondary jaw to within a radius of 1mm. Methods: Utilizing a self-leveling laser, the Elekta ball (BB) bearing phantom (8mm steel ball), the Modus QA Isocenter Cube software, and a colleague-provided isocenter alignment method, the kV, table mechanical, and HexaPOD isocenters were localized to the MV isocenter. Isocenter coincidence was tested using the Isocenter Cube from Modus QA, brought to kV isocenter using CBCT and the HexaPOD system. MV images were taken at various gantry, collimator, and couch angles and then analyzed with the aforementioned software to determine coincidence of the 5mm steel ball at cube center with MV isocenter. To improve overall coincidence, two errors were addressed iteratively: (1) LINAC mechanical and radiation isocenter coincidence allowing each isocenter volume to have similar variations during gantry and collimator rotation and (2) collimator rotational walkout which reduced the size of both mechanical and radiation isocenters. Beam steering was performed to bring MV isocenter closer to mechanical and collimator walkout was adjusted by physically shifting the MLC bank. Initial procedures were repeated to align all isocenters and perform regular checks for consistency. Results: Post-initial alignment revealed a maximum diameter of 1.8mm for MV isocenter and maximum isocenter alignment error of up to 1.22mm radius which improved to roughly 1.0mm MV isocenter diameter and <0.71mm radius alignment error with a consistency within 0.25mm. Conclusion: With the methods described, all isocenters were brought into alignment within a radius of 1mm.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2015

TU-AB-303-08: GPU-Based Software Platform for Efficient Image-Guided Adaptive Radiation Therapy

Purpose: In this study, we develop an integrated software platform for adaptive radiation therapy (ART) that combines fast and accurate image registration, segmentation, and dose computation/accumulation methods. Methods: The proposed system consists of three key components; 1) deformable image registration (DIR), 2) automatic segmentation, and 3) dose computation/accumulation. The computationally intensive modules including DIR and dose computation have been implemented on a graphics processing unit (GPU). All required patient-specific data including the planning CT (pCT) with contours, daily cone-beam CTs, and treatment plan are automatically queried and retrieved from their own databases. To improve the accuracy of DIR between pCT and CBCTs, we use the double force demons DIR algorithm in combination with iterative CBCT intensity correction by local intensity histogram matching. Segmentation of daily CBCT is then obtained by propagating contours from the pCT. Daily dose delivered to the patient is computed on the registered pCT by a GPU-accelerated superposition/convolution algorithm. Finally, computed daily doses are accumulated to show the total delivered dose to date. Results: Since the accuracy of DIR critically affects the quality of the other processes, we first evaluated our DIR method on eight head-and-neck cancer cases and compared its performance. Normalized mutual-information (NMI) and normalized cross-correlation (NCC) computed as similarity measures, and our method produced overall NMI of 0.663 and NCC of 0.987, outperforming conventional methods by 3.8% and 1.9%, respectively. Experimental results show that our registration method is more consistent and roust than existing algorithms, and also computationally efficient. Computation time at each fraction took around one minute (30–50 seconds for registration and 15–25 seconds for dose computation). Conclusion: We developed an integrated GPU-accelerated software platform that enables accurate and efficient DIR, auto-segmentation, and dose computation, thus supporting an efficient ART workflow. This work was supported by NIH/NCI under grant R42CA137886.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

VERA and VERA-EDU 3.5 Release Notes

The Virtual Environment for Reactor Applications components included in this distribution include selected computational tools and supporting infrastructure that solve neutronics, thermal-hydraulics, fuel performance, and coupled neutronics-thermal hydraulics problems. The infrastructure components provide a simplified common user input capability and provide for the physics integration with data transfer and coupled-physics iterative solution algorithms. Neutronics analysis can be performed for 2D lattices, 2D core and 3D core problems for pressurized water reactor geometries that can be used to calculate criticality and fission rate distributions by pin for input fuel compositions. MPACT uses the Method of Characteristics transport approach for 2D problems. For 3D problems, MPACT uses the 2D/1D method which uses 2D MOC in a radial plane and diffusion or SPn in the axial direction. MPACT includes integrated cross section capabilities that provide problem-specific cross sections generated using the subgroup methodology. The code can be executed both 2D and 3D problems in parallel to reduce overall run time. A thermal-hydraulics capability is provided with CTF (an updated version of COBRA-TF) that allows thermal-hydraulics analyses for single and multiple assemblies using the simplified VERA common input. This distribution also includes coupled neutronics/thermal-hydraulics capabilities to allow calculations using MPACT coupled with CTF. The VERA fuel rod performance component BISON calculates, on a 2D or 3D basis, fuel rod temperature, fuel rod internal pressure, free gas volume, clad integrity and fuel rod waterside diameter. These capabilities allow simulation of power cycling, fuel conditioning and deconditioning, high burnup performance, power uprate scoping studies, and accident performance. Input/Output capabilities include the VERA Common Input (VERAIn) script which converts the ASCII common input file to the intermediate XML used to drive all of the physics codes in the VERA Core Simulator (VERA-CS). VERA component codes either input the VERA XML format directly, or provide a preprocessor which can convert the XML into native input. VERAView is an interactive graphical interface for the visualization and engineering analyses of output data from VERA. The python-based software is easy to install and intuitive to use, and provides instantaneous 2D and 3D images, 1D plots, and alpha-numeric data from VERA multi-physics simulations. Testing within CASL has focused primarily on Westinghouse four-loop reactor geometries and conditions with example problems included in the distribution.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Towards universal unfolding of detector effects in high-energy physics using denoising diffusion probabilistic models

Correcting for detector effects in experimental data, particularly through unfolding, is critical for enabling precision measurements in high-energy physics. However, traditional unfolding methods face challenges in scalability, flexibility, and dependence on simulations. We introduce a novel approach to multidimensional object-wise unfolding using conditional Denoising Diffusion Probabilistic Models (cDDPM). Our method utilizes the cDDPM for a non-iterative, flexible posterior sampling approach, incorporating distribution moments as conditioning information, which exhibits a strong inductive bias that allows it to generalize to unseen physics processes without explicitly assuming the underlying distribution. Our results highlight the potential of this method as a step towards a "universal" unfolding tool that reduces dependence on truth-level assumptions, while enabling the unfolding of a wide range of measured distributions with improved adaptability and accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

SU-F-P-45: Clinical Experience with Radiation Dose Reduction of CT Examinations Using Iterative Reconstruction Algorithms

Purpose: Iterative reconstruction (IR) algorithms have been adopted by medical centers in the past several years. IR has a potential to substantially reduce patient dose while maintaining or improving image quality. This study characterizes dose reductions in clinical settings for CT examinations using IR. Methods: We retrospectively analyzed dose information from patients who underwent abdomen/pelvis CT examinations with and without contrast media in multiple locations of our Healthcare system. A total of 743 patients scanned with ASIR on 64 slice GE lightspeed VCTs at three sites, and 30 patients scanned with SAFIRE on a Siemens 128 slice Definition Flash in one site was retrieved. For comparison, patient data (n=291) from a GE scanner and patient data (n=61) from two Siemens scanners where filtered back-projection (FBP) was used was collected retrospectively. 30% and 10% ASIR, and SAFIRE Level 2 was used. CTDIvol, Dose-length-product (DLP), weight and height from all patients was recorded. Body mass index (BMI) was calculated accordingly. To convert CTDIvol to SSDE, AP and lateral dimensions at the mid-liver level was measured for each patient. Results: Compared with FBP, 30% ASIR reduces dose by 44.1% (SSDE: 12.19mGy vs. 21.83mGy), while 10% ASIR reduced dose by 20.6% (SSDE 17.32mGy vs. 21.83). Use of SAFIRE reduced dose by 61.4% (SSDE: 8.77mGy vs. 22.7mGy). The geometric mean for patients scanned with ASIR was larger than for patients scanned with FBP (geometric mean is 297.48 mmm vs. 284.76 mm). The same trend was observed for the Siemens scanner where SAFIRE was used (geometric mean: 316 mm with SAFIRE vs. 239 mm with FBP). Patient size differences suggest that further dose reduction is possible. Conclusion: Our data confirmed that in clinical practice IR can significantly reduce dose to patients who undergo CT examinations, while meeting diagnostic requirements for image quality.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-DE-207A-01: Impact of Statistical Weights On Detection of Low-Contrast Details in Model-Based Iterative CT Reconstruction

Purpose: Penalized-weighted least-square reconstruction has become an important research topic in CT, to reduce dose without affecting image quality. Two components impact image quality in this reconstruction: the statistical weights and the use of an edge-preserving penalty term. We are interested in assessing the influence of statistical weights on their own, without the edge-preserving feature. Methods: The influence of statistical weights on image quality was assessed in terms of low-contrast detail detection using LROC analysis. The task amounted to detect and localize a 6-mm lesion with random contrast inside the FORBILD head phantom. A two-alternative forced-choice experiment was used with two human observers performing the task. Reconstructions without and with statistical weights were compared, both using the same quadratic penalty term. The beam energy was set to 30keV to amplify spatial differences in attenuation and thereby the role of statistical weights. A fan-beam data acquisition geometry was used. Results: Visual inspection of images clearly showed a difference in noise between the two reconstructions methods. As expected, the reconstruction without statistical weights exhibited noise streaks. The other reconstruction appeared better in this aspect, but presented other disturbing noise patterns and artifacts induced by the weights. The LROC analysis yield the following 95-percent confidence interval for the difference in reader-averaged AUC (reconstruction without weights minus reconstruction with weights): [0.0026,0.0599]. The mean AUC value was 0.9094. Conclusion: We have investigated the impact of statistical weights without the use of edge-preserving penalty in penalized weighted least-square reconstruction. A decrease rather than increase in image quality was observed when using statistical weights. Thus, the observers were better able to cope with the noise streaks than the noise patterns and artifacts induced by the statistical weights. It may be that different results would be obtained if the penalty term was used with a pixel-dependent weight. F Noo receives research support from Siemens Healthcare GmbH.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Fast meta-solvers for 3D complex-shape scatterers using neural operators trained on a non-scattering problem

Three-dimensional target identification using scattering techniques requires high accuracy solutions and very fast computations for real-time predictions in some critical applications. We first train a deep neural operator (DeepONet) to solve wave propagation problems described by the Helmholtz equation in a domain without scatterers but at different wavenumbers and with a complex absorbing boundary condition. We then design two classes of fast meta-solvers by combining DeepONet with either relaxation methods, such as Jacobi and Gauss-Seidel, or with Krylov methods, such as GMRES and BiCGStab, using the trunk basis of DeepONet as a coarse-scale preconditioner. We leverage the spectral bias of neural networks to account for the lower part of the spectrum in the error distribution while the upper part is handled inexpensively using relaxation methods or fine-scale preconditioners. The meta-solvers are then applied to solve scattering problems with different shape of scatterers, at no extra training cost. We first demonstrate that the resulting meta-solvers are shape-agnostic, fast, and robust, whereas the standard standalone solvers may even fail to converge without the DeepONet. We then apply both classes of meta-solvers to scattering from a submarine, a complex three-dimensional problem. We achieve very fast solutions, especially with the DeepONet-Krylov methods, which require orders of magnitude fewer iterations than any of the standalone solvers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

A computational approach for hypersonic nonequilibrium radiation utilizing space partition algorithm and Gauss quadrature

An efficient computational capability for nonequilibrium radiation simulation via the ray tracing technique has been accomplished. The radiative rate equation is iteratively coupled with the aerodynamic conservation laws including nonequilibrium chemical and chemical–physical kinetic models. The spectral properties along tracing rays are determined by a space partition algorithm of the nearest neighbor search process, and the numerical accuracy is further enhanced by a local resolution refinement using the Gauss–Lobatto polynomial. The interdisciplinary governing equations are solved by an implicit delta formulation through the diminishing residual approach. The axisymmetric radiating flow fields over the reentry RAM-CII probe have been simulated and verified with flight data and previous solutions by traditional methods. A computational efficiency gain nearly forty times is realized over that of the existing simulation procedures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Non-equilibrium STLS approach to transport properties of single impurity Anderson model

In this work, using the non-equilibrium Keldysh formalism, we study the effects of the electron–electron interaction and the electron-spin correlation on the non-equilibrium Kondo effect and the transport properties of the symmetric single impurity Anderson model (SIAM) at zero temperature by generalizing the self-consistent method of Singwi, Tosi, Land, and Sjolander (STLS) for a single-band tight-binding model with Hubbard type interaction to out of equilibrium steady-states. We at first determine in a self-consistent manner the non-equilibrium spin correlation function, the effective Hubbard interaction, and the double-occupancy at the impurity site. Then, using the non-equilibrium STLS spin polarization function in the non-equilibrium formalism of the iterative perturbation theory (IPT) of Yosida and Yamada, and Horvatic and Zlatic, we compute the spectral density, the current–voltage characteristics and the differential conductance as functions of the applied bias and the strength of on-site Hubbard interaction. We compare our spectral densities at zero bias with the results of numerical renormalization group (NRG) and depict the effects of the electron–electron interaction and electron-spin correlation at the impurity site on the aforementioned properties by comparing our numerical result with the order U{sup 2} IPT. Finally, we show that the obtained numerical results on the differential conductance have a quadratic universal scaling behavior and the resulting Kondo temperature shows an exponential behavior. -- Highlights: •We introduce for the first time the non-equilibrium method of STLS for Hubbard type models. •We determine the transport properties of SIAM using the non-equilibrium STLS method. •We compare our results with order-U2 IPT and NRG. •We show that non-equilibrium STLS, contrary to the GW and self-consistent RPA, produces the two Hubbard peaks in DOS. •We show that the method keeps the universal scaling behavior and correct exponential behavior of Kondo temperature.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Probability of Initiation in Neutron Transport

We discuss the numerical solution of the nonlinear integro-differential equation for the probability of a divergent neutron chain in a stationary system (i.e., the probability of initiation (POI)). We follow the development described in Bell’s classic paper on the stochastic theory of neutron transport. As noted by Bell, the linearized form of this equation resembles the linear adjoint neutron transport equation. A matrix formalism for the discretized steady state (or forward) neutron equation in slab geometry is first developed and is then used to derive the discrete adjoint equation. A main advantage of this discrete development is that the resulting discrete adjoint equation does not depend upon how the multigroup cross sections for the forward problem are obtained. That is, we derive the discrete adjoint directly from the discrete forward equations rather than discretizing directly the adjoint equation. This also guarantees that the discrete adjoint operator is consistent with the inner product used to define the adjoint operator. We discuss three approaches for the numerical solution of the POI equations, and present numerical results on several test problems. The three solution methods are a simple fixed-point iteration, a second approach that is akin to a nonlinear Power iteration, and a third approach which uses a Newton-Krylov nonlinear solver. We also give sufficient conditions to guarantee the existence and uniqueness of nontrivial solutions to our discrete POI equations when the discrete system is supercritical, and that only the trivial solution exists when the discrete system is subcritical. Our approach is modeled after the analysis presented for the continuous POI equations by Mokhtar-Kharroubi and Jarmouni-Idrissi, and by Pazy and Rabinowitz.

42 ENGINEERING↗