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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Preliminary Phase Field Computational Model Development

This interim report presents progress towards the development of meso-scale models of magnetic behavior that incorporate microstructural information. Modeling magnetic signatures in irradiated materials with complex microstructures (such as structural steels) is a significant challenge. The complexity is addressed incrementally, using the monocrystalline Fe (i.e., ferrite) film as model systems to develop and validate initial models, followed by polycrystalline Fe films, and by more complicated and representative alloys. In addition, the modeling incrementally addresses inclusion of other major phases (e.g., martensite, austenite), minor magnetic phases (e.g., carbides, FeCr precipitates), and minor nonmagnetic phases (e.g., Cu precipitates, voids). The focus of the magnetic modeling is on phase-field models. The models are based on the numerical solution to the Landau-Lifshitz-Gilbert equation. From the computational standpoint, phase-field modeling allows the simulation of large enough systems that relevant defect structures and their effects on functional properties like magnetism can be simulated. To date, two phase-field models have been generated in support of this work. First, a bulk iron model with periodic boundary conditions was generated as a proof-of-concept to investigate major loop effects of single versus polycrystalline bulk iron and effects of single non-magnetic defects. More recently, to support the experimental program herein using iron thin films, a new model was generated that uses finite boundary conditions representing surfaces and edges. This model has provided key insights into the domain structures observed in magnetic force microscopy (MFM) measurements. Simulation results for single crystal thin-film iron indicate the feasibility of the model for determining magnetic domain wall thickness and mobility in an externally applied field. Because the phase-field model dimensions are limited relative to the size of most specimens used in experiments, special experimental methods were devised to create similar boundary conditions in the iron films. Preliminary MFM studies conducted on single and polycrystalline iron films with small sub-areas created with focused ion beam have correlated quite well qualitatively with phase-field simulations. However, phase-field model dimensions are still small relative to experiments thus far. We are in the process of increasing the size of the models and decreasing specimen size so both have identical dimensions. Ongoing research is focused on validation of the phase-field model. Validation is being accomplished through comparison with experimentally obtained MFM images (in progress), and planned measurements of major hysteresis loops and first order reversal curves. Extrapolation of simulation sizes to represent a more stochastic bulk-like system will require sampling of various simulations (i.e., with single non-magnetic defect, single magnetic defect, single grain boundary, single dislocation, etc.) with distributions of input parameters. These outputs can then be compared to laboratory magnetic measurements and ultimately to simulate magnetic Barkhausen noise signals.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Hydrate-filled Fracture Formation at Keathley Canyon 151, Gulf of Mexico, and Implications for Non-vent Sites

Near-vertical hydrate-filled fractures are found in subseafloor marine muds, at both advective methane vent sites and at sites without obvious methane and fluid advection (non-vent sites). At non-vent sites, the mechanisms that transport methane to the fractures and control how hydrate-filled fractures form are not well understood. However, these mechanisms are important to establish, as most of Earth's natural gas hydrate is likely bound in marine mud systems. In this work, we focus on understanding the origin of hydrate and how fracture form at non-vent sites by examining previously hydrate-bearing fractures in conventional cores taken from Keathley Canyon 151, U.S. northern Gulf of Mexico, drilled by the Gas Hydrate Joint Industry Project in 2005. We combine information from well logs, sediment cores, and science party results and add new X-ray computed tomography of archival sections and scanning electron microcopy of core samples to develop a conceptual model. We propose that locally generated microbial methane is transported via diffusion from small pores in marine mud into biomineralized burrows with larger pore size in a process called short-range migration. Hydrate forms in burrows once the methane diffuses into them and the dissolved methane concentration exceeds the solubility threshold. When hydrate fills a burrow, heave from additional hydrate growth places stress on the burrow edges, expands the fracture, and creates additional void space in which methane can diffuse and continue forming hydrate. Fractures slowly propagate in the direction of maximum principal stress.

58 GEOSCIENCES↗
DOE OSTI2019

Gyrokinetic simulations of m=0 mode in sheared flow Z-pinch

Axisymmetric stability properties of sheared flow Z-pinch plasmas are studied by making use of the gyrokinetic approximation in the long-wavelength limit. Numerical simulations are carried out with the high-order finite-volume code COntinuum Gyrokinetic Edge New Technology (COGENT) and are analyzed for the parameters characteristic of the FuZE experiment. Reduction of the linear growth rate with increasing shear is observed, and the results are elucidated by making use of a local dispersion relation analysis. In addition, COGENT simulations are compared with fully kinetic particle-in-cell simulations, and with an ideal magnetohydrodynamics (MHD) model. Good agreement between the gyrokinetic and fully kinetic results for the linear stability is found, with the gyrokinetic model requiring much less computational time due to its ability to step over particle gyroperiod. The ideal MHD model is found to be consistent with the kinetic models in the long-wavelength part of the spectra ($kρ_i$), while failing to adequately predict short-scale ($kρ_i$) stability. Here, $k$ is the axial wavelength vector and $ρ_i$ is the ion gyroradius.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Realizing symmetry-protected topological phases in a spin-1/2 chain with next-nearest-neighbor hopping on superconducting qubits

Quantum simulation on near-term quantum hardware is a topic of intense interest. The preparation of novel quantum states of matter provides a quantitative assessment of the capabilities of near-term digital quantum computers to implement circuits with structure of relevance to quantum simulation. Here, we conduct a benchmark study by realizing symmetry-protected topological (SPT) phases of a spin-1/2 Hamiltonian with next-nearest-neighbor hopping on up to 11 qubits on a programmable superconducting quantum processor using adiabatic state preparation. Using recompilation techniques to reduce the gate count to around 50 two-qubit gates, we observe clear signatures of the two distinct SPT phases, such as excitations localized to specific edges and finite string-order parameters. Finally, we identify a parasitic phase associated with the two-qubit gate as the dominant imperfection that limits the depth of the circuits, indicating a research topic of interest for future hardware development.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Characterizing Sierra Nevada Snowpack Using Variable-Resolution CESM

The location, timing, and intermittency of precipitation in California make the state integrally reliant on winter-season snowpack accumulation to maintain its economic and agricultural livelihood. Of particular concern is that winter-season snowpack has shown a net decline across the western United States over the past 50 years, resulting in major uncertainty in water-resource management heading into the next century. Cutting-edge tools are available to help navigate and preemptively plan for these uncertainties. This paper uses a next-generation modeling technique-variable-resolution global climate modeling within the Community Earth System Model (VR-CESM)-at horizontal resolutions of 0.125° (14 km) and 0.25° (28 km). VR-CESM provides the means to include dynamically large-scale atmosphere-ocean drivers, to limit model bias, and to provide more accurate representations of regional topography while doing so in a more computationally efficient manner than can be achieved with conventional general circulation models. This paper validates VR-CESM at climatological and seasonal time scales for Sierra Nevada snowpack metrics by comparing them with the "Daymet," "Cal-Adapt," NARR, NCEP, and North American Land Data Assimilation System (NLDAS) reanalysis datasets, the MODIS remote sensing dataset, the SNOTEL observational dataset, a standard-practice global climate model (CESM), and a regional climate model (WRF Model) dataset. Overall, given California's complex terrain and intermittent precipitation and that both of the VR-CESM simulations were only constrained by prescribed sea surface temperatures and data on sea ice extent, a 0.68 centered Pearson product-moment correlation, a negative mean SWE bias of < 7 mm, an interquartile range well within the values exhibited in the reanalysis datasets, and a mean December-February extent of snow cover that is within 7% of the expected MODIS value together make apparent the efficacy of the VR-CESM framework.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Theoretical Plasma Physics

Lattice Boltzmann algorithms are a mesoscopic method to solve problems in nonlinear physics which are highly parallelized – unlike the direction solution of the original problem. These methods are applied to both fluid and magnetohydrodynamic turbulence. By introducing entropic constraints one can enforce the positive definiteness of the distribution functions and so be able to simulate fluids at high Reynolds numbers without numerical instabilities. By introducing a vector distribution function for the magnetic field one can enforce the divergence free condition on the magnetic field automatically, without the need of divergence cleaning as needed in most direct numerical solutions of the resistive magnetohydrodynamic equations. The principal reason for the high parallelization of lattice Boltzmann codes is that they consist of a kinetic collisional relaxation step (which is purely local) followed by a simple shift of the relaxed data to neighboring lattice sites. In large eddy simulations, the closure schemes are highly nonlocal – the most famous of these schemes is that due to Smagorinsky. Under a lattice Boltzmann representation the Smagorinsky closure is purely local – being simply a particular moment on the perturbed distribution fucntions. After nonlocal fluid moment models were discovered to represent Landau damping, it was found possible to model these fluid models using an appropriate lattice Boltzmann algorithm. The close to ideal parallelization of the lattice Boltzmann codes permitted us to be Gordon Bell finalists on using the Earth Simulation in Japan. We have also been involved in the radio frequency propagation of waves into a tokamak and into a spherical overdense tokamak plasma. Initially we investigated the use of a quasi-optical grill for the launching of lower hybrid waves into a tokamak. It was found that the conducting walls do not prevent the rods from being properly irradiated, the overloading of the quasi-optical grill is not severe with the electric field only being about three times higher than in the ideal case. Moreover, the quasi-optical grill was significantly fewer structural elements that the multijunction grill. Nevertheless there has not been much interest from experimental fusion groups to implementing these structures. Hence we have returned to optimizing the multijunction grill so that the large number of coupling matrix elements can be efficiently evaluated using symmetry arguments. In overdense plasmas, the standard electromagnetic waves cannot propagate into the plasma center, but are reflected at the plasma edge. By optimizing mode conversion processes (in particular, the O-X-B wave propagation of Ordinary Mode converting to an Extraordinary mode which then converts into an electrostatic Bernstein wave) one can excite within the plasma an electrostatic Bernstein wave that does not suffer density cutoffs and is absorbed on the electron cyclotron harmonics. Finally we have started looking at other mesoscopic lattice algorithms that involve unitary collision and streaming steps. Because these algorithms are unitary they can be run on quantum computers when they become available – unlike their computational cousin of lattice Boltzmann which is a purely classical code. These quantum lattice gas algorithms have been tested successfully on exact analytic soliton collision solution. These calculations are hoped to be able to study Bose Einstein condensed atomic gases and their ground states in an optical lattice.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

SCIDAC Center for simulation of wave particle interactions CompX participation

Harnessing the energy that is released in fusion reactions would provide a safe and abundant source of power to meet the growing energy needs of the world population. The next step toward the development of fusion as a practical energy source is the construction of ITER, a device capable of producing and controlling the high performance plasma required for self-sustaining fusion reactions, or “burning” plasma. The input power required to drive the ITER plasma into the burning regime will be supplied primarily with a combination of external power from radio frequency waves in the ion cyclotron range of frequencies and energetic ions from neutral beam injection sources, in addition to internally generated Ohmic heating from the induced plasma current that also serves to create the magnetic equilibrium for the discharge. The ITER project is a large multi-billion dollar international project in which the US participates. The success of the ITER project depends critically on the ability to create and maintain burning plasma conditions, it is absolutely necessary to have physics-based models that can accurately simulate the RF processes that affect the dynamical evolution of the ITER discharge. The Center for Simulation of WavePlasma Interactions (CSWPI), also known as RF-SciDAC, is a multi-institutional collaboration that has conducted ongoing research aimed at developing: (1) Coupled core-to-edge simulations that will lead to an increased understanding of parasitic losses of the applied RF power in the boundary plasma between the RF antenna and the core plasma; (2) Development of models for core interactions of RF waves with energetic electrons and ions (including fusion alpha particles and fast neutral beam ions) that include a more accurate representation of the particle dynamics in the combined equilibrium and wave fields; and (3) Development of improved algorithms that will take advantage of massively parallel computing platforms at the petascale level and beyond to achieve the needed physics, resolution, and/or statistics to address these issues. CompX provides computer codes and analysis for the calculation of the electron and ion distributions in velocity-space and plasma radius which are necessary for reliable calculations of power deposition and toroidal current drive due to combined radiofrequency and neutral beam at high injected powers. It has also contributed to ray tracing modeling of injected radiofrequency powers, and to coupling between full-wave radiofrequency wave models and the distribution function calculations. In the course of this research, the Fokker-Planck distribution function calculation was made substantially more realistic by inclusion of finite-width drift-orbit effects (FOW). FOW effects were also implemented in a calculation of the phase-space diffusion resulting from radiofrequency full-wave models. Average level of funding for CompX was approximately three man-months per year.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Final Technical Report for Grant No. DE-FC02-01ER54648, SciDAC Center for Simulation of Wave-Plasma Interactions

Harnessing the energy that is released in fusion reactions would provide a safe and abundant source of power to meet the growing energy needs of the world population. The next step toward the development of fusion as a practical energy source is the construction of ITER, a device capable of producing and controlling the high performance plasma required for self-sustaining fusion reactions, or “burning” plasma. The input power required to drive the ITER plasma into the burning regime will be supplied primarily with a combination of external power from radio frequency waves in the ion cyclotron range of frequencies and energetic ions from neutral beam injection sources, in addition to internally-generated Ohmic heating from the induced plasma current that also serves to create the magnetic equilibrium for the discharge. Since the success of the ITER project depends critically on the ability to create and maintain burning plasma conditions, it is absolutely necessary to have physics-based models that can accurately simulate the RF processes that affect the dynamical evolution of the ITER discharge. The Center for Simulation of Wave-Plasma Interactions (CSWPI) is a multi-institutional collaboration that has conducted ongoing research aimed at developing: (1) Coupled core-to-edge simulations that will lead to an increased understanding of parasitic losses of the applied RF power in the boundary plasma between the RF antenna and the core plasma; (2) Development of models for core interactions of RF waves with energetic electrons and ions (including fusion alpha particles and fast neutral beam ions) that include a more accurate representation of the particle dynamics in the combined equilibrium and wave fields; and (3) Development of improved algorithms that will take advantage of massively parallel computing platforms at the petascale level and beyond to achieve the needed physics, resolution, and/or statistics to address these issues. This research reported in this final technical report is focused on further verification and validation of simulation models for interactions of RF waves with energetic particles in the core with a long term goal of assessing their readiness for inclusion in integrated modeling frameworks and utilizing the world’s largest supercomputers to quantitatively predict the detailed electric field structure in the vicinity of the launching structures.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Basic Research in Edge and Scrape-Off Layer Fusion Plasmas (Final Report)

U.S. Department of Energy (DOE) supported work at Lodestar Research Corporation under grant DE-FG02-97ER54392 is summarized in this final report. The research conducted under this grant addressed key scientific issues associated with boundary plasmas in fusion energy experimental devices. Harnessing the energy that is released in fusion reactions would provide a safe and abundant source of power to meet the growing energy needs of the world population. Lodestar investigated the important cm-scale region near the edge of these devices where hot plasma, close to one million degrees, meets material surfaces in what is known as a scrape-off layer (SOL). This critical region is subject to plasma turbulence and plasma flows which must be understood to optimize fusion performance on future machines. Strong interactions of applied RF waves is also observed to occur in this region, and must be understood to mitigate unwanted effects and enhance overall performance. The work employed theoretical models and theory-based computational models for validation. The models were applied to understand experimental results and to carry out basic theoretical investigations relevant to the production of fusion energy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Variational principles with Padé approximants for tearing mode analysis

Tearing modes occur in several distinct physical regimes, and it is often important to compute the inner layer response for these modes with various effects. There is a need for an approximate and efficient method of solving the inner layer equations in all these regimes. In this paper, we introduce a method of solving the inner layer equations based on using a variational principle with Padé approximants. For all the regimes considered, the main layer equations to be solved are inhomogeneous, and Padé approximants give a convenient and efficient method of satisfying the correct asymptotic behavior at the edge of the layer. Results using this variational principle—Padé approximant method in three of these regimes is presented. These regimes are the constant-ψ resistive-inertial (RI) regime, the constant-ψ viscoresistive regime, and the non-constant-ψ inviscid tearing regime. The last regime includes the constant-ψ RI regime and the inertial regime. The results show that reasonable accuracy can be obtained very efficiently with Padé approximants having a small number of parameters.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Collisional transport across the magnetic field in drift-fluid models

Drift ordered fluid models are widely applied in studies of low-frequency turbulence in the edge and scrape-off layer regions of magnetically confined plasmas. Here, we show how collisional transport across the magnetic field is self-consistently incorporated into drift-fluid models without altering the drift-fluid energy integral. We demonstrate that the inclusion of collisional transport in drift-fluid models gives rise to diffusion of particle density, momentum, and pressures in drift-fluid turbulence models and, thereby, obviates the customary use of artificial diffusion in turbulence simulations. We further derive a computationally efficient, two-dimensional model, which can be time integrated for several turbulence de-correlation times using only limited computational resources. The model describes interchange turbulence in a two-dimensional plane perpendicular to the magnetic field located at the outboard midplane of a tokamak. The model domain has two regions modeling open and closed field lines. The model employs a computational expedient model for collisional transport. Numerical simulations show good agreement between the full and the simplified model for collisional transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Incremental Interval Assignment (IIA) for Scalable Mesh Preparation

Interval Assignment (IA) means selecting the number of mesh edges for each CAD curve. IIA is a discrete algorithm over integers. A priority queue iteratively selects compatible sets of intervals to increase in lock-step by integers. In contrast, the current capability in Cubit is floating-point Linear Programming with Branch-and-Bound for integerization (BBIA).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Verification, Validation, and Calibration Through a Causal Lens

While typical validation and verification approaches focus on identifying the associations between data elements using statistical and machine learning methods, the novel methods in this paper focus instead on identifying causal relationships between data elements. Statistical and machine-learning-based approaches are strictly data-driven, meaning that they provide quantitative comparison measures between data sets without explicitly considering the hypotheses behind them. This can lead to the erroneous conclusion that, if two data sets are close enough, the models that generated them are similar. In addition, when experimental and simulated data differ to an extent that fails to meet the acceptance criteria, calibration techniques are used to tweak simulation model parameters to reduce the gap between the two types of data. This produces the false expectation that a simulation model will match reality. The methods presented in this paper move away from these strictly data-driven methods for validation and calibration toward more robust, model-driven methods based on causal inference. Causal inference aims to identify the possible mechanisms that might have generated data. Thus, this analysis targets the prediction of the effects when one (or more) of the identified mechanisms are altered. There are many approaches to identify, quantify, and illustrate causal relationships. For the scope of this paper, directed graphs are employed as causal models. If the directed graph lacks cycles, it is known as a directed acyclic graph. A node in such a graph represents an observed data element while a directed edge connecting two nodes represents a causal relationship between two variables. The developed causal methods are designed to extract causal models from simulation models and experimental data. Causal models capture the causal relationships between data elements (e.g., simulated and experimental data). In this context, validation and verification are performed by comparing causal models. The proposed approach does not only inform system analysts on how a simulation model matches real-world data, but also identifies elements of the simulation model that should be revised when discrepancies between simulation and experimental data are observed. Through these causal methods, analysts can identify the portion of the model equation(s) that are behind an edge connecting two variables. Hence, once the structural differences between causal models have been determined, model calibration can occur by changing only those model parameters that impact the identified causal relationships.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

VALIDATION, VERIFICATION, AND CALIBRATION THROUGH A CAUSAL LENS

This paper presents an alternative method based on causal inference to perform validation, verification, and calibration of simulation models. While classical validation and verification approaches focus on the identification of the associations between data elements using statistical and machine learning methods, the novel methods in this paper focus instead on the identification of causal relationships between data elements. Statistical and machine learning-based approaches are strictly data-driven, meaning that they provide quantitative comparison measures between datasets without explicitly considering the hypotheses behind them. This can lead to the erroneous conclusion that, if two data sets are close enough, then the models that generated them are similar. In addition, when experimental and simulated data differ to an extent that fails to meet the acceptance criteria, calibration techniques are used to tweak simulation model parameters to reduce the gap between the two types of data. This produces the false expectation that a simulation model will match reality. The methods presented in this paper move away from these strictly data-driven methods for validation and calibration toward more robust, model-driven methods based on causal inference. Causal inference aims to identify the possible mechanisms that might have generated data. Thus, this analysis targets the prediction of the effects when one (or more) of the identified mechanisms are altered. There are many approaches to identify, quantify and illustrate causal relationships. For the scope of this paper, directed graphs are employed as causal models. If the directed graph lacks cycles it is known as a directed acyclic graph (DAG). A node in such a graph represents an observed data element while a directed edge connecting two nodes represents a causal relationship between two variables. The developed causal methods are designed to extract causal models from simulation models and from experimental data. Causal models capture the causal relationships between data elements (e.g., simulated and experimental data). In this context, validation and verification are performed by comparing causal models. The proposed approach does not only inform system analysts on how a simulation model matches real-world data, but also identifies elements of the simulation model that should be revised when discrepancies between simulation and experimental data are observed. Through these causal methods, analysts have a means to identify the portion of the model equation(s) that are behind an edge connecting two variables. Hence, once the structural differences between causal models have been determined, model calibration can occur by changing only those model parameters that impact the identified causal relationships.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Transcatheter Arterial Embolization with a Mixture of Absolute Ethanol and Iodized Oil for Poorly Visualized Endophytic Renal Masses Prior to CT-Guided Percutaneous Cryoablation

PurposeTo retrospectively evaluate the feasibility of transcatheter arterial embolization (TAE) using a mixture of absolute ethanol and iodized oil to improve localization of endophytic renal masses on unenhanced computed tomography (CT) prior to CT-guided percutaneous cryoablation (PCA).Materials and MethodsOur institutional review board approved this retrospective study. From September 2011 to June 2015, 17 patients (mean age, 66.8 years) with stage T1a endophytic renal masses (mean diameter, 26.5 mm) underwent TAE using a mixture of absolute ethanol and iodized oil to improve visualization of small and endophytic renal masses on unenhanced CT prior to CT-guided PCA. TAE was considered successful that accumulated iodized oil depicted whole of the tumor edge on CT. PCA was considered successful when the iceball covered the entire tumor with over a 5 mm margin. Oncological and renal functional outcomes and complications were also evaluated.ResultsTAE was successfully performed in 16 of 17 endophytic tumors. The 16 tumors were performed under CT-guided PCA with their distinct visualization of localization and safe ablated margin. During the mean follow-up period of 15.4 ± 5.1 months, one patient developed local recurrence. Estimated glomerular filtration rate declined by 8 % with statistical significance (P = 0.01). There was no procedure-related significant complication.ConclusionTAE using a mixture of absolute ethanol and iodized oil to improve visualization of endophytic renal masses facilitated tumor localization on unenhanced CT, permitting depiction of the tumor edge as well as a safe margin for ablation during CT-guided PCA, with an acceptable decline in renal function.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Data fusion in X-ray computed tomography using a superiorization approach

X-ray computed tomography (CT) is an important and widespread inspection technique in industrial non-destructive testing. However, large-sized and heavily absorbing objects cause artifacts due to either the lack of penetration of the specimen in specific directions or by having data from only a limited angular range of views. In such cases, valuable information about the specimen is not revealed by the CT measurements alone. Further imaging modalities, such as optical scanning and ultrasonic testing, are able to provide data (such as an edge map) that are complementary to the CT acquisition. In this paper, a superiorization approach (a newly developed method for constrained optimization) is used to incorporate the complementary data into the CT reconstruction; this allows precise localization of edges that are not resolvable from the CT data by itself. Superiorization, as presented in this paper, exploits the fact that the simultaneous algebraic reconstruction technique (SART), often used for CT reconstruction, is resilient to perturbations; i.e., it can be modified to produce an output that is as consistent with the CT measurements as the output of unmodified SART, but is more consistent with the complementary data. The application of this superiorized SART method to measured data of a turbine blade demonstrates a clear improvement in the quality of the reconstructed image.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2012

A Multithreaded Algorithm for Network Alignment Via Approximate Matching

Network alignment is an optimization problem to find the best one-to-one map between the vertices of a pair of graphs that overlaps in as many edges as possible. It is a relaxation of the graph isomorphism problem and is closely related to the subgraph isomorphism problem. The best current approaches are entirely heuristic, and are iterative in nature. They generate real-valued heuristic approximations that must be rounded to find integer solutions. This rounding requires solving a bipartite maximum weight matching problem at each step in order to avoid missing high quality solutions. We investigate substituting a parallel, half-approximation for maximum weight matching instead of an exact computation. Our experiments show that the resulting difference in solution quality is negligible. We demonstrate almost a 20-fold speedup using 40 threads on an 8 processor Intel Xeon E7-8870 system (from 10 minutes to 36 seconds).

network alignment, matching, multicore↗
DOE OSTI2018

Identifying Backbones in Three-Dimensional Discrete Fracture Networks: A Bipartite Graph-Based Approach

In this paper, we present a graph-based method to identify primary flow and transport sub-networks in three-dimensional discrete fracture networks (DFNs). The structure of a DFN lends itself to the use of graphs as a coarse-scale representation that retains the multiscale nature of flow and transport through fracture media. We develop a bipartite graph representation that integrates fracture network topology, fracture geometry, and hydraulic properties. We show that the two most common graph-representations of DFNs, vertices representing intersections and vertices representing fractures, are projections of this bipartite graph thereby providing a generalization of previous DFN-graph frameworks. The primary subnetworks in each DFN are identified by running a heuristic algorithm that determines the edge-disjoint shortest paths through the graph which correspond to the regions where the fastest transport occurs. The method does not have any user-defined parameters and terminates in a finite number of steps. The quality of the method is demonstrated by comparing transport simulations on the identified primary subnetwork and full network, which are in good agreement for early and middle times. In conclusion, these estimates of the first passage times can be achieved with close to an order of magnitude reduction of computational expense using the proposed method.

58 GEOSCIENCES↗