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

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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Regularized Finite Element Formulations for Shear Band Instabilities in Metals

In my research I have addressed several fundamental issues of dynamic fracture: 1. established the role of heat conduction as a natural regularizing mechanism in shearband problems (i.e. using the correct physics for this problem), 2. developed a unified model to incorporate fracture through a modified phase field formulation, 3. developed stability analysis tools to determine the onset of localization, 4. developed discretization methods and solvers to solve this problem (on parallel computers) that lead to mesh insensitive results and fast convergence. For such difficult problems, the physics and numerics are strongly coupled. To accurately model the physics, one must develop reliable numerics but reliable numerics depends on correct description of the physics. To this end, we have already made significant progress in the field showing that a fully-coupled implicit solution with heat conduction is the key to obtain reliable results for shear bands (see the next sections for more details). This research fits well within the mission of DOE ASCR program on all aspects: from governing equations to discretization to solvers to parallel computers to applications problems. It also relies on the computational tools developed through the SciDAC institutes FASTMath and SDAV, such as PETSc (and SLEPc), ParaView, Trilinos and Masquite.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Robust Size-Effects Compensation Through Regularized Lever-Arm Estimation

Size effects are an unavoidable nuisance in inertial navigation using sensors which are not co-located at the navigational point of interest. When estimating transforms between the navigation point and sensor locations, some trajectories preclude observation of all model parameters. Regularization is proposed to avoid over-fitting size-effects models. The result yields robust size effects compensation in other regions of flight.

42 ENGINEERING↗
DOE OSTI2023

A spatially regularized detector for emergent/re-emergent disease outbreaks

Early detection of outbreaks caused by emergent pathogens, using epidemiological surveillance data i.e., daily case counts, is difficult. This is because the data tend to be noisy during the early epoch of the outbreak. In contrast, the spread-rate of the disease tends to be well-behaved, as it depends only on the mixing patterns of the population and the characteristics of the pathogen, neither of which behave erratically in space-time. In this report, we explore whether the spread-rate can be used for epidemiological surveillance, conditional on case count data. Estimating the spread-rate from case count data allows us to exploit exogenous information, e.g., incubation period distributions etc., which can considerably smooth out any erratic temporal behavior. Further, epidemiological dynamics are spatially correlated, and if case counts are available for multiple areal units e.g., counties, these correlations could potentially be used to suppress noise in the early epoch data. These exogenous information and structure are not exploited by conventional syndromic surveillance detectors to extract a well-behaved latent variable for monitoring purposes. The technical challenge lies in the estimation of the spread-rate field jointly over a collection of areal units; further, the spread-rate varies over time. We develop a method based on mean-field variational inference to approximately estimate the spread-rate field, using a Gaussian Random Field Model for spatial regularization. The method is tested on the estimation of spread-rate in the thirty-three counties of New Mexico and detect the arrival of the Fall 2020 COVID-19 wave in September 2020. We find that the method is scalable, but underestimates the uncertainty in the estimated spread-rate field. We detect the arrival of the Fall 2020 wave a week ahead of conventional syndromic surveillance algorithms, but our simplistic detection algorithm, based on simple anomaly detection, suffers from a high false positive rate, similar to conventional detectors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Ultrasonic Model-Based Iterative Reconstruction with Spatially Variant Regularization for One-Sided Non-Destructive Evaluation

One-sided ultrasonic non-destructive evaluation (UNDE) uses ultrasound signals to investigate and inspect structures that are only accessible from one side. A widely used reconstruction technique in UNDE is the synthetic aperture focusing technique (SAFT). SAFT produces fast reconstruction and reasonable images for simple structures. However, for large complex structures, SAFT reconstructions suffer from noise and artifacts. To resolve some of the drawbacks of SAFT, an ultrasonic model-based iterative reconstruction (MBIR) algorithm, a method based on Bayesian estimation, was proposed that showed significant enhancement over SAFT in reducing noise and artifacts. In this paper, we build on previous investigations of the use of MBIR reconstruction on ultrasound data by proposing a spatially varying prior-model to account for artifacts from deeper regions and a 3D regularizer to account for correlations between scans from adjacent regions. We demonstrate that the use of the new prior model in MBIR can significantly improve reconstructions compared to SAFT and the previously proposed MBIR technique.

Almansouri, Hani↗
DOE OSTI2021

Cardinality-Regularized Hawkes-Granger Model

We propose a new sparse Granger-causal learning framework for temporal event data. We focus on a specific class of point processes called the Hawkes process. We begin by pointing out that most of the existing sparse causal learning algorithms for the Hawkes process suffer from a singularity in maximum likelihood estimation. As a result, their sparse solutions can appear only as numerical artifacts. In this paper, we propose a mathematically well-defined sparse causal learning framework based on a cardinality-regularized Hawkes process, which remedies the pathological issues of existing approaches. We leverage the proposed algorithm for the task of instance-wise causal event analysis, where sparsity plays a critical role. We validate the proposed framework with two real use-cases, one from the power grid and the other from the cloud data center management domain.

Ide, Tsuyoshi↗
DOE OSTI2017

An exhaustive survey of regular peptide conformations using a new metric for backbone handedness ( h )

The Ramachandran plot is important to structural biology as it describes a peptide backbone in the context of its dominant degrees of freedom—the backbone dihedral angles φ and ψ (Ramachandran, Ramakrishnan & Sasisekharan, 1963). Since its introduction, the Ramachandran plot has been a crucial tool to characterize protein backbone features. However, the conformation or twist of a backbone as a function of φ and ψ has not been completely described for both cis and trans backbones. Additionally, little intuitive understanding is available about a peptide’s conformation simply from knowing the φ and ψ values of a peptide (e.g., is the regular peptide defined by φ = ψ = - 100° left-handed or right-handed?). This report provides a new metric for backbone handedness ( h ) based on interpreting a peptide backbone as a helix with axial displacement d and angular displacement θ , both of which are derived from a peptide backbone’s internal coordinates, especially dihedral angles φ , ψ and ω . In particular, h equals sin( θ ) d / d |, with range [-1, 1] and negative (or positive) values indicating left(or right)-handedness. The metric h is used to characterize the handedness of every region of the Ramachandran plot for both cis ( ω = 0°) and trans ( ω = 180°) backbones, which provides the first exhaustive survey of twist handedness in Ramachandran ( φ , ψ ) space. These maps fill in the ‘dead space’ within the Ramachandran plot, which are regions that are not commonly accessed by structured proteins, but which may be accessible to intrinsically disordered proteins, short peptide fragments, and protein mimics such as peptoids. Finally, building on the work of (Zacharias & Knapp, 2013), this report presents a new plot based on d and θ that serves as a universal and intuitive alternative to the Ramachandran plot. The universality arises from the fact that the co-inhabitants of such a plot include every possible peptide backbone including cis and trans backbones. The intuitiveness arises from the fact that d and θ provide, at a glance, numerous aspects of the backbone including compactness, handedness, and planarity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Constructing a logical, regular axis topology from an irregular topology

Constructing a logical regular topology from an irregular topology including, for each axial dimension and recursively, for each compute node in a subcommunicator until returning to a first node: adding to a logical line of the axial dimension a neighbor specified in a nearest neighbor list; calling the added compute node; determining, by the called node, whether any neighbor in the node's nearest neighbor list is available to add to the logical line; if a neighbor in the called compute node's nearest neighbor list is available to add to the logical line, adding, by the called compute node to the logical line, any neighbor in the called compute node's nearest neighbor list for the axial dimension not already added to the logical line; and, if no neighbor in the called compute node's nearest neighbor list is available to add to the logical line, returning to the calling compute node.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Constructing a logical, regular axis topology from an irregular topology

Constructing a logical regular topology from an irregular topology including, for each axial dimension and recursively, for each compute node in a subcommunicator until returning to a first node: adding to a logical line of the axial dimension a neighbor specified in a nearest neighbor list; calling the added compute node; determining, by the called node, whether any neighbor in the node's nearest neighbor list is available to add to the logical line; if a neighbor in the called compute node's nearest neighbor list is available to add to the logical line, adding, by the called compute node to the logical line, any neighbor in the called compute node's nearest neighbor list for the axial dimension not already added to the logical line; and, if no neighbor in the called compute node's nearest neighbor list is available to add to the logical line, returning to the calling compute node.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Metal-assisted etch combined with regularizing etch

In an aspect of the disclosure, a process for forming nanostructuring on a silicon-containing substrate is provided. The process comprises (a) performing metal-assisted chemical etching on the substrate, (b) performing a clean, including partial or total removal of the metal used to assist the chemical etch, and (c) performing an isotropic or substantially isotropic chemical etch subsequently to the metal-assisted chemical etch of step (a). In an alternative aspect of the disclosure, the process comprises (a) performing metal-assisted chemical etching on the substrate, (b) cleaning the substrate, including removal of some or all of the assisting metal, and (c) performing a chemical etch which results in regularized openings in the silicon substrate.

42 ENGINEERING↗
DOE OSTI2018

Detecting and quantifying materials in containers utilizing an inverse algorithm with adaptive regularization

A method, system and computer program product for automatically detecting and quantifying materials in containers (e.g., luggage, storage containers, equipment or componentry for processing or handling). An X-ray radiograph of a container is generated. A set of materials of interest (e.g., plutonium, steel) is selected to determine if the object comprises or contains materials of interest. An estimate of the areal densities or thicknesses of each of the selected materials of interest is obtained by minimizing an objective function with respect to the areal densities or thicknesses for each of the selected materials of interest. Adaptive regularization is implemented in the objective function to improve optimization results by adding a constraint to the objective function, where the constraint penalizes the objective function for solutions that do not line up with a prior belief about the solution form (e.g., the solution should not be negative or especially noisy).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Hydrodynamic Analysis of a Suspended Cylinder Under Regular Wave Loading Based on Computational Fluid Dynamics: Preprint

An investigation into the computation of hydrodynamic loads on a suspended cylinder in regular waves is presented. The primary goal was to perform a three-way-validation of the loads between experimental measurements and simulations from two computational methods. Experimental measurements of the longitudinal inline force on a cylinder suspended at a fixed po- sition were available from the Offshore Code Comparison Col- laboration, Continued, with Correlation (OC5) project, Phase Ia. These measurements were compared to Computational Fluid Dynamics (CFD) simulations based on the solution of Reynolds- averaged Navier-Stokes (RANS) equations, as implemented in STAR-CCM plus. The study encompassed a sensitivity analysis of the loads computed in STAR-CCM plus based on wave modeling, boundary conditions, turbulence modeling, and spatial and tem- poral discretization. The analysis was supplemented by results generated with the offshore wind turbine engineering software OpenFAST, based on a hybrid combination of second-order po- tential flow and viscous drag fromMorison's equation. The focus of the investigation was on the assessment of the accuracy of the computation of first- and higher-order hydrodynamic loads. Sub- stantial differences were observed in the numerical prediction of the second and third harmonic force contribution. Local flow field analysis with CFD was applied to study the physics of wave run-up and diffraction dynamics to identify the causes.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Metal-assisted etch combined with regularizing etch

In an aspect of the disclosure, a process for forming nanostructuring on a silicon-containing substrate is provided. The process comprises (a) performing metal-assisted chemical etching on the substrate, (b) performing a clean, including partial or total removal of the metal used to assist the chemical etch, and (c) performing an isotropic or substantially isotropic chemical etch subsequently to the metal-assisted chemical etch of step (a). In an alternative aspect of the disclosure, the process comprises (a) performing metal-assisted chemical etching on the substrate, (b) cleaning the substrate, including removal of some or all of the assisting metal, and (c) performing a chemical etch which results in regularized openings in the silicon substrate.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Provably optimal parallel transport sweeps on regular grids

We have found provably optimal algorithms for full-domain discrete-ordinate transport sweeps on regular grids in 3D Cartesian geometry. We describe these algorithms and sketch a 'proof that they always execute the full eight-octant sweep in the minimum possible number of stages for a given P{sub x} x P{sub y} x P{sub z} partitioning. Computational results demonstrate that our optimal scheduling algorithms execute sweeps in the minimum possible stage count. Observed parallel efficiencies agree well with our performance model. An older version of our PDT transport code achieves almost 80% parallel efficiency on 131,072 cores, on a weak-scaling problem with only one energy group, 80 directions, and 4096 cells/core. A newer version is less efficient at present-we are still improving its implementation - but achieves almost 60% parallel efficiency on 393,216 cores. These results conclusively demonstrate that sweeps can perform with high efficiency on core counts approaching 10{sup 6}. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Use of Separator with Regular Granular Filling in Extraction Processes - 12209

The separator with a regular granular filling has been developed to be used for the operations of the removal of carbon-black impurities from the aqueous flow; the intra-cycle regeneration of back-extractants; and the concentrating back-extraction of plutonium in the extraction SNF reprocessing technology. The process conditions for those operations have been experimentally tested using this separator. Thus, the separator for operations of concentrating reextraction of plutonium and regeneration recycling extractant allows to: - derive plutonium from the organic stream into an extremely concentrated form, reducing the amount of liquid radioactive waste (raffinate, decantate) plutonium branches to a minimum; - controlling the processes of concentration of uranium and plutonium, get uranium-plutonium product with required concentration and the amount of metal with required ratio; - eliminate contamination of the emulsion flows; - simplify the purification of uranium from the extract plutonium; - test results showed that when working on a solution 'hydrazine-DTPA' in the separator it is achieved the extraction of plutonium re-extract - 82% TC - at 56-65%. With the transition to the reextraction by solution 'U (IV)-hydrazine', of plutonium into re-extract increases to 95%, technetium - up to 83%; - regenerate the extractant recycling minimizing the amount of liquid radioactive waste generated as a technology used as well as alternative 'salt-free' systems; - it is found that the regeneration of the extractant solution of soda and EDA in the separator at a load of 3.2 m{sup 3} / (m{sup 2}.h) it can be achieved almost complete phase separation. Residual carryover of 0,005-0,006% emulsion is on the verge of analytical detection. - It is shown that in the depth of separation phase a separation of the extractant regeneration of quality superior is more than 5-7 times to the extraction. (authors)

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

Deep Learning with Physics Priors as Generalized Regularizers

In various scientific and engineering applications, there is typically an approximate model of the underlying complex system, even though it contains both aleatoric and epistemic uncertainties. In this paper, we present a principled method to incorporate these approximate models as physics priors in modeling, to prevent overfitting and enhancing the generalization capabilities of the trained models. Utilizing the structural risk minimization (SRM) inductive principle pioneered by Vapnik, this approach structures the physics priors into generalized regularizers. The experimental results demonstrate that our method achieves up to two orders of magnitude of improvement in testing accuracy.

Liu, Frank↗
DOE OSTI2024

Spectral Analysis of Regular Material Point Method and its Application to Study High Pressure Reverse Osmosis Membrane Compaction and Embossing

Material Point Method (MPM) is gaining widespread interest in applied continuum mechanics. The fact that all the continuum properties are stored on the particles (or material points) and the governing equations are solved on these material points makes MPM extremely suited to problems involving severe material deformations, such as crack propagation, soil movement, and fluid flows. Despite its popularity, only a few studies have focused on the numerical properties of MPM. This presentation introduces a global spectral analysis of the regular material point method. Contrary to previous studies, the analysis focuses on the numerical properties of the method in the spectral space. The amplification factor is derived as a function of the non- dimensional wave numbers. It provides insights into the stability and dissipative properties of the method for various CFL and Fourier numbers. The effect of the grid shape functions, number of particles per cell and their locations inside the grid cell are also analyzed. The EXAGOOP MPM solver (https://github.com/NREL/Exagoop.git) is developed at the National Renewable Energy Laboratory as a part of the NAWI UHPRO project and is based on the AMReX framework. A single-level, uniform cartesian grid is used as the background mesh, while the particle class in AMReX is used to manage the material point operations. Linear hat and B-splines are used as grid shape functions, while the time integration is performed using explicit Euler time integration. EXAGOOP is both CPU and GPU compatible and has been demonstrated to work well on multiple compute architectures. The performance of EXAGOOP on various computing architectures is presented along with its application to study compaction and embossing of high-pressure reverse osmosis membranes. The MPM solution accurately reproduces the membrane deformation. The deformed pore size and structure simulated using MPM also agree well with experimental SEM images.

material point method↗