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

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Inhibition of atomic layer deposition of TiO 2 by functionalizing silicon surface with 4-fluorophenylboronic acid

As the size of the components in electronic devices decreases, new approaches and chemical modification schemes are needed to produce nanometer-size features with bottom-up manufacturing. Organic monolayers can be used as effective resists to block the growth of materials on non-growth substrates in area-selective deposition methods. However, choosing the appropriate surface modification requires knowledge of the corresponding chemistry and also a detailed investigation of the behavior of the functionalized surface in realistic deposition schemes. This study aims to investigate the chemistry of boronic acids that can be used to prepare such non-growth areas on elemental semiconductors. 4-Fluorophenylboronic acid is used as a model to investigate the possibility to utilize the Si(100) surface functionalized with this compound as a non-growth substrate in a titanium dioxide (TiO 2 ) deposition scheme based on sequential doses of tetrakis(dimethylamido)titanium and water. Here, a combination of X-ray photoelectron spectroscopy and time-of-flight secondary ion mass spectrometry allows for a better understanding of the process. The resulting surface is shown to be an effective non-growth area to TiO 2 deposition when compared to currently used H-terminated silicon surfaces but to exhibit much higher stability in ambient conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

T2-weighted four dimensional magnetic resonance imaging with result-driven phase sorting

Purpose: T2-weighted MRI provides excellent tumor-to-tissue contrast for target volume delineation in radiation therapy treatment planning. This study aims at developing a novel T2-weighted retrospective four dimensional magnetic resonance imaging (4D-MRI) phase sorting technique for imaging organ/tumor respiratory motion. Methods: A 2D fast T2-weighted half-Fourier acquisition single-shot turbo spin-echo MR sequence was used for image acquisition of 4D-MRI, with a frame rate of 2–3 frames/s. Respiratory motion was measured using an external breathing monitoring device. A phase sorting method was developed to sort the images by their corresponding respiratory phases. Besides, a result-driven strategy was applied to effectively utilize redundant images in the case when multiple images were allocated to a bin. This strategy, selecting the image with minimal amplitude error, will generate the most representative 4D-MRI. Since we are using a different image acquisition mode for 4D imaging (the sequential image acquisition scheme) with the conventionally used cine or helical image acquisition scheme, the 4D dataset sufficient condition was not obviously and directly predictable. An important challenge of the proposed technique was to determine the number of repeated scans (N{sub R}) required to obtain sufficient phase information at each slice position. To tackle this challenge, the authors first conducted computer simulations using real-time position management respiratory signals of the 29 cancer patients under an IRB-approved retrospective study to derive the relationships between N{sub R} and the following factors: number of slices (N{sub S}), number of 4D-MRI respiratory bins (N{sub B}), and starting phase at image acquisition (P{sub 0}). To validate the authors’ technique, 4D-MRI acquisition and reconstruction were simulated on a 4D digital extended cardiac-torso (XCAT) human phantom using simulation derived parameters. Twelve healthy volunteers were involved in an IRB-approved study to investigate the feasibility of this technique. Results: 4D data acquisition completeness (C{sub p}) increases as NR increases in an inverse-exponential fashion (C{sub p} = 100 − 99 × exp(−0.18 × N{sub R}), when N{sub B} = 6, fitted using 29 patients’ data). The N{sub R} required for 4D-MRI reconstruction (defined as achieving 95% completeness, C{sub p} = 95%, N{sub R} = N{sub R,95}) is proportional to N{sub B} (N{sub R,95} ∼ 2.86 × N{sub B}, r = 1.0), but independent of N{sub S} and P{sub 0}. Simulated XCAT 4D-MRI showed a clear pattern of respiratory motion. Tumor motion trajectories measured on 4D-MRI were comparable to the average input signal, with a mean relative amplitude error of 2.7% ± 2.9%. Reconstructed 4D-MRI for healthy volunteers illustrated clear respiratory motion on three orthogonal planes, with minimal image artifacts. The artifacts were presumably caused by breathing irregularity and incompleteness of data acquisition (95% acquired only). The mean relative amplitude error between critical structure trajectory and average breathing curve for 12 healthy volunteers is 2.5 ± 0.3 mm in superior–inferior direction. Conclusions: A novel T2-weighted retrospective phase sorting 4D-MRI technique has been developed and successfully applied on digital phantom and healthy volunteers.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Multigrid Reduction in Time for Nonlinear Parabolic Problems: A Case Study

The need for parallelism in the time dimension is being driven by changes in computer architectures, where performance increases are now provided through greater concurrency, not faster clock speeds. This creates a bottleneck for sequential time marching schemes because they lack parallelism in the time dimension. Multigrid reduction in time (MGRIT) is an iterative procedure that allows for temporal parallelism by utilizing multigrid reduction techniques and a multilevel hierarchy of coarse time grids. MGRIT has been shown to be effective for linear problems, with speedups of up to 50 times. The goal of this work is the efficient solution of nonlinear problems with MGRIT, where efficiency is defined as achieving similar performance when compared to an equivalent linear problem. The benchmark nonlinear problem is the p-Laplacian, where p=4 corresponds to a well-known nonlinear diffusion equation and p=2 corresponds to the standard linear diffusion operator, our benchmark linear problem. The key difficulty encountered is that the nonlinear time-step solver becomes progressively more expensive on coarser time levels as the time-step size increases. To overcome such difficulties, multigrid research has historically targeted an accumulated body of experience regarding how to choose an appropriate solver for a specific problem type. To that end, this paper develops a library of MGRIT optimizations and modifications, most important an alternate initial guess for the nonlinear time-step solver and delayed spatial coarsening, that will allow many nonlinear parabolic problems to be solved with parallel scaling behavior comparable to the corresponding linear problem.

parareal↗
DOE OSTI2016

Multigrid Reduction in Time for Nonlinear Parabolic Problems

The need for parallel-in-time is being driven by changes in computer architectures, where future speed-ups will be available through greater concurrency, but not faster clock speeds, which are stagnant.This leads to a bottleneck for sequential time marching schemes, because they lack parallelism in the time dimension. Multigrid Reduction in Time (MGRIT) is an iterative procedure that allows for temporal parallelism by utilizing multigrid reduction techniques and a multilevel hierarchy of coarse time grids. MGRIT has been shown to be effective for linear problems, with speedups of up to 50 times. The goal of this work is the efficient solution of nonlinear problems with MGRIT, where efficient is defined as achieving similar performance when compared to a corresponding linear problem. As our benchmark, we use the p-Laplacian, where p = 4 corresponds to a well-known nonlinear diffusion equation and p = 2 corresponds to our benchmark linear diffusion problem. When considering linear problems and implicit methods, the use of optimal spatial solvers such as spatial multigrid imply that the cost of one time step evaluation is fixed across temporal levels, which have a large variation in time step sizes. This is not the case for nonlinear problems, where the work required increases dramatically on coarser time grids, where relatively large time steps lead to worse conditioned nonlinear solves and increased nonlinear iteration counts per time step evaluation. This is the key difficulty explored by this paper. We show that by using a variety of strategies, most importantly, spatial coarsening and an alternate initial guess to the nonlinear time-step solver, we can reduce the work per time step evaluation over all temporal levels to a range similar with the corresponding linear problem. This allows for parallel scaling behavior comparable to the corresponding linear problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Crop physiology calibration in the CLM

Farming is using more of the land surface, as population increases and agriculture is increasingly applied for non-nutritional purposes such as biofuel production. This agricultural expansion exerts an increasing impact on the terrestrial carbon cycle. In order to understand the impact of such processes, the Community Land Model (CLM) has been augmented with a CLM-Crop extension that simulates the development of three crop types: maize, soybean, and spring wheat. The CLM-Crop model is a complex system that relies on a suite of parametric inputs that govern plant growth under a given atmospheric forcing and available resources. CLM-Crop development used measurements of gross primary productivity (GPP) and net ecosystem exchange (NEE) from AmeriFlux sites to choose parameter values that optimize crop productivity in the model. In this paper, we calibrate these parameters for one crop type, soybean, in order to provide a faithful projection in terms of both plant development and net carbon exchange. Calibration is performed in a Bayesian framework by developing a scalable and adaptive scheme based on sequential Monte Carlo (SMC). The model showed significant improvement of crop productivity with the new calibrated parameters. We demonstrate that the calibrated parameters are applicable across alternative years and different sites.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1985

Interface shape in Czochralski grown crystals - Effect of conduction and radiation

A sequential modular computational scheme has been proposed for the calculation of temperature profiles in the melt and crystal including the melt-crystal interface shape and the crystal pulling rate for a fixed crystal radius. The heat transfer in the melt is assumed to occur by conduction only. The shape of melt-gas meniscus, described by Laplace-Young equation, is incorporated in the model and its effects on interface shape and pulling rate are examined. Further, the model incorporates the detailed radiation interaction among the various surfaces in the puller using the Gebhart enclosure theory which accounts for both direct and reflected radiation. The effects of various process parameters on the interface shape and the pulling rate have been investigated. The results of this study indicate that the shape of the melt-gas meniscus has a significant effect on the pulling rate and the interface shape in conformity with earlier studies. Further, it is shown that a simple radiation model (Stefan's model) is inadequate to model the radiation heat exchange in the Czochralski puller apparatus and the detailed Gebhart analysis is necessary for accurate calculation of both the temperature profile in the crystal as well as the interface shape.

Srivastava, R. K.↗
NASA NTRS1991

Robust contour decomposition using a constant curvature criterion

The problem of decomposing an extended boundary or contour into simple primitives is addressed with particular emphasis on Laplacian-of-Gaussian (LoG) zero-crossing contours. A technique is introduced for partitioning such contours into constant curvature segments. A nonlinear `blip' filter matched to the impairment signature of the curvature computation process, an overlapped voting scheme, and a sequential contiguous segment extraction mechanism are used. This technique is insensitive to reasonable changes in algorithm parameters and robust to noise and minor viewpoint-induced distortions in the contour shape, such as those encountered between stereo image pairs. The results vary smoothly with the data, and local perturbations induce only local changes in the result. Robustness and insensitivity are experimentally verified.

Wuescher, Daniel M.↗
DOE OSTI2022

Multi-axis Accelerometry and Rotation Sensing using a Point Source Atom Interferometer

A point source atom interferometer (PSI) is a device where atoms are split and recombined by applying a temporal sequence of Raman pulses during the expansion of a cloud of cold atoms behaving approximately as a point source. Unlike a conventional light pulse atom interferometer, the PSI can produce a signal that corresponds to multi-axis rotation only, independent of acceleration. In addition, it can be used to measure acceleration along one direction, independent of rotation. Here, we describe a modified PSI that can be used to measure multi-axis rotation and multi-axis acceleration. Specifically, this type of PSI can be used to measure two-axes rotation around the directions perpendicular to the light pulses, as well as the acceleration in all three directions, with only one pair of Raman beams. Using two pairs of Raman beams in orthogonal directions sequentially, such a scheme would enable the realization of a complete atom interferometric inertial measurement unit.

Li, Jinyang↗
DOE OSTI2024

Probing vibronic coherence in charge migration in molecules using strong-field sequential double ionization

We propose a scheme for probing vibronic coherence in charge migration in molecules utilizing strong-field sequential double ionization. To demonstrate the feasibility of this approach, we perform full simulations of a pump-probe scheme employing few-cycle intense infrared pulses for N 2 and O 2 . We predict that the vibronic coherence between the pumped states will be directly imprinted in experimental observables such as kinetic energy release spectra and branching ratios of the dissociative dications. Our simulations are based on the recently developed density matrix approach for sequential double ionization model, which is capable of efficiently accounting for molecular orientations and enabling direct comparison with experimental results. Lastly, our findings strongly encourage the use of this probing scheme in future charge migration experiments.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS1992

Unsteady, one-dimensional gas dynamics computations using a TVD type sequential solver

The efficacy of high resolution convection schemes to resolve sharp gradient in unsteady, 1D flows is examined using the TVD concept based on a sequential solution algorithm. Two unsteady flow problems are considered which include the problem involving the interaction of the various waves in a shock tube with closed reflecting ends and the problem involving the unsteady gas dynamics in a tube with closed ends subject to an initial pressure perturbation. It is concluded that high accuracy convection schemes in a sequential solution framework are capable of resolving discontinuities in unsteady flows involving complex gas dynamics. However, a sufficient amount of dissipation is required to suppress oscillations near discontinuities in the sequential approach, which leads to smearing of the solution profiles.

Thakur, Siddharth↗
NASA NTRS2010

Aerosol Observability and Predictability: From Research to Operations for Chemical Weather Forecasting. Lagrangian Displacement Ensembles for Aerosol Data Assimilation

A challenge common to many constituent data assimilation applications is the fact that one observes a much smaller fraction of the phase space that one wishes to estimate. For example, remotely sensed estimates of the column average concentrations are available, while one is faced with the problem of estimating 3D concentrations for initializing a prognostic model. This problem is exacerbated in the case of aerosols because the observable Aerosol Optical Depth (AOD) is not only a column integrated quantity, but it also sums over a large number of species (dust, sea-salt, carbonaceous and sulfate aerosols. An aerosol transport model when driven by high-resolution, state-of-the-art analysis of meteorological fields and realistic emissions can produce skillful forecasts even when no aerosol data is assimilated. The main task of aerosol data assimilation is to address the bias arising from inaccurate emissions, and Lagrangian misplacement of plumes induced by errors in the driving meteorological fields. As long as one decouples the meteorological and aerosol assimilation as we do here, the classic baroclinic growth of error is no longer the main order of business. We will describe an aerosol data assimilation scheme in which the analysis update step is conducted in observation space, using an adaptive maximum-likelihood scheme for estimating background errors in AOD space. This scheme includes e explicit sequential bias estimation as in Dee and da Silva. Unlikely existing aerosol data assimilation schemes we do not obtain analysis increments of the 3D concentrations by scaling the background profiles. Instead we explore the Lagrangian characteristics of the problem for generating local displacement ensembles. These high-resolution state-dependent ensembles are then used to parameterize the background errors and generate 3D aerosol increments. The algorithm has computational complexity running at a resolution of 1/4 degree, globally. We will present the result of assimilating AOD retrievals from MODIS (on both Aqua and TERRA satellites) from AERONET for validation. The impact on the GEOS-5 Aerosol Forecasting will be fully documented.

da Silva, Arlindo↗
NASA NTRS2008

Fault-Tolerant Coding for State Machines

Two reliable fault-tolerant coding schemes have been proposed for state machines that are used in field-programmable gate arrays and application-specific integrated circuits to implement sequential logic functions. The schemes apply to strings of bits in state registers, which are typically implemented in practice as assemblies of flip-flop circuits. If a single-event upset (SEU, a radiation-induced change in the bit in one flip-flop) occurs in a state register, the state machine that contains the register could go into an erroneous state or could hang, by which is meant that the machine could remain in undefined states indefinitely. The proposed fault-tolerant coding schemes are intended to prevent the state machine from going into an erroneous or hang state when an SEU occurs. To ensure reliability of the state machine, the coding scheme for bits in the state register must satisfy the following criteria: 1. All possible states are defined. 2. An SEU brings the state machine to a known state. 3. There is no possibility of a hang state. 4. No false state is entered. 5. An SEU exerts no effect on the state machine. Fault-tolerant coding schemes that have been commonly used include binary encoding and "one-hot" encoding. Binary encoding is the simplest state machine encoding and satisfies criteria 1 through 3 if all possible states are defined. Binary encoding is a binary count of the state machine number in sequence; the table represents an eight-state example. In one-hot encoding, N bits are used to represent N states: All except one of the bits in a string are 0, and the position of the 1 in the string represents the state. With proper circuit design, one-hot encoding can satisfy criteria 1 through 4. Unfortunately, the requirement to use N bits to represent N states makes one-hot coding inefficient.

Naegle, Stephanie Taft↗
NASA NTRS1972

A universal functional object

A scheme is presented for realizing any function, combinational or sequential, in a single universal function scheme, termed the universal function object UF. This scheme is addressed to the problem of the proliferation of the number of parts (cards, chips) necessary for conventional implementation in an LSI technology of a computer system. The UF implementation will use about ten times more circuits than a conventional implementation regardless of the size of the design. The UF approach also includes general-purpose spares for failing circuits. The procedure could be used both at manufacture to increase yields, as well as to achieve automatic repair.

Roth, J. P.↗
DOE OSTI2022

Accelerating astronomical and cosmological inference with preconditioned Monte Carlo

ABSTRACT We introduce preconditioned Monte Carlo (PMC), a novel Monte Carlo method for Bayesian inference that facilitates efficient sampling of probability distributions with non-trivial geometry. PMC utilizes a Normalizing Flow (NF) in order to decorrelate the parameters of the distribution and then proceeds by sampling from the preconditioned target distribution using an adaptive Sequential Monte Carlo (SMC) scheme. The results produced by PMC include samples from the posterior distribution and an estimate of the model evidence that can be used for parameter inference and model comparison, respectively. The aforementioned framework has been thoroughly tested in a variety of challenging target distributions achieving state-of-the-art sampling performance. In the cases of primordial feature analysis and gravitational wave inference, PMC is approximately 50 and 25 times faster, respectively, than nested sampling (NS). We found that in higher dimensional applications, the acceleration is even greater. Finally, PMC is directly parallelisable, manifesting linear scaling up to thousands of CPUs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Multigrid Reduction in Time for Chaotic Dynamical Systems

As CPU clock speeds have stagnated and high performance computers continue to have ever higher core counts, increased parallelism is needed to take advantage of these new architectures. Traditional serial time-marching schemes can be a significant bottleneck, as many types of simulations require large numbers of time-steps which must be computed sequentially. Parallel-in-time schemes, such as the Multigrid Reduction in Time (MGRIT) method, remedy this by parallelizing across time-steps and have shown promising results for parabolic problems. However, chaotic problems have proved more difficult, since chaotic initial value problems (IVPs) are inherently ill-conditioned. MGRIT relies on a hierarchy of successively coarser time-grids to iteratively correct the solution on the finest time-grid, but due to the nature of chaotic systems, small inaccuracies on the coarser levels can be greatly magnified and lead to poor coarse-grid corrections. Here we introduce a modified MGRIT algorithm based on an existing quadratically converging nonlinear extension to the multigrid Full Approximation Scheme (FAS), as well as a novel time-coarsening scheme. Together, these approaches better capture long-term chaotic behavior on coarse-grids and greatly improve convergence of MGRIT for chaotic IVPs. Further, we introduce a novel low-memory variant of the algorithm for solving chaotic PDEs with MGRIT which not only solves the IVP, but also provides estimates for the unstable Lyapunov vectors of the system. Finally, we provide supporting numerical results for the Lorenz system and demonstrate parallel speedup for the chaotic Kuramoto–Sivashinsky PDE over a significantly longer time-domain than in previous works.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1982

Kalman filtering for spacecraft attitude estimation

Several schemes in current use for sequential estimation of spacecraft attitude using Kalman filters are examined. These differ according to their treatment of the attitude error, namely: using the complete four-component quaternion; using a truncated quaternion in which one of the components has been eliminated; or using a quaternion referred to approximate body-fixed axes. These schemes are examined for the case of a spacecraft carrying line-of-sight attitude sensors and three-axis gyros whose measurements are corrupted by noise on both the drift rate and the drift-rate ramp. The analysis of the covariance is carried out in detail. The historical development of Kalman filtering of attitude is reviewed.

Lefferts, E. J.↗